Noel Cressie: Research Publications

These are divided up into the following categories and can be accessed by clicking on the links below:




Wikle, C.K., Zammit-Mangion, A., and Cressie, N. (2019). Spatio-Temporal Statistics with R. Chapman & Hall/CRC, Boca Raton, FL (380 pp.).


Cressie, N. and Wikle, C.K. (2011). Statistics for Spatio-Temporal Data. Wiley, Hoboken, NJ (588 pp.).


Cressie, N. (1993). Statistics for Spatial Data, rev. edn. Wiley, New York, NY (900 pp.). (Original edition, 1991. Paperback edition in the Wiley Classics Library: Wiley, Hoboken, NJ, 2015).


Read, T.R.C. and Cressie, N. (1988). Goodness-of-Fit Statistics for Discrete Multivariate Data. Springer, New York, NY (211 pp.).


Refereed Articles


Bertolacci, M., Zammit-Mangion, A., Schuh, A., Bukosa, B., Fisher, J. A., Cao, Y., Kaushik, A., and Cressie, N. (2024). Inferring changes to the global carbon cycle with WOMBAT v2.0, a hierarchical flux-inversion framework (with Supplement). The Annals of Applied Statistics, 18, 303–327 (doi:10.1214/23-AOAS1790).

Pearse, A. R., Cressie, N., and Gunawan, D. (2024). Optimal prediction of positive-valued spatial processes: Asymmetric power-divergence loss.  Spatial Statistics60, 100829 (doi:10.1016/j.spasta.2024.100829).

Sainsbury-Dale, M., Zammit-Mangion, A., and Cressie, N. (2024). Modeling big, heterogeneous, non-Gaussian spatial and spatio-temporal data using FRK. Journal of Statistical Software, 108 (10), 1- 39 (doi:10.18637/jss.v108.i10).

Zammit-Mangion, A., Kaminski, M. D., Tran, B-H., Filippone, M., and Cressie, N. (2024). Spatial Bayesian neural networks. Spatial Statistics60, 100825 (doi:10.1016/j.spasta.2024.100825).


Cressie, N. (2023). Decisions, decisions, decisions in an uncertain environment. Environmetrics, 34, e2767 (doi:10.1002/env.2767).

Cressie, N. (2023). Adapting statistical science for a fast-changing climate. CHANCE, 36.1, 9-13 (doi:10.1080/09332480.2023.2179263).

Cressie, N. and Moores, M. T. (2023). Spatial statistics, in Encyclopedia of Mathematical Geosciences, eds B. S. Daya Sagar, Q. Cheng, J. McKinley, and F. Agterberg. Springer, Cham, CH, pp.1362-1373 (2023) (doi:10.1007/978-3-030-26050-7_31-2).

Cressie, N., Zammit-Mangion, A., Jacobson, J., and Bertolacci, M. (2023). Earth’s CO2 battle: a view from space. Significance, 20, February 2023, 14-19 (doi:10.1093/jrssig/qmad003).

Byrne, B. et al. (with 60 co-authors including Cressie, N.). (2023). National CO2 budgets (2015-2020) inferred from atmospheric CO2 observations in support of the global stocktake. Earth System Science Data, 15, 963-1004 (doi:10.5194/essd-15-963-2023).

Gaubert, B. et al. (with 30 co-authors including Cressie, N.). (2023). Neutral tropical African CO2 exchange estimated from aircraft and satellite observations. Global Biogeochemical Cycles, 37, 1-19 (doi:10.1029/2023GB007804).

Jacobson, J., Cressie, N., and Zammit-Mangion, A. (2023). Spatial statistical prediction of solar-induced chlorophyll fluorescence (SIF) from multivariate OCO-2 dataRemote Sensing, 15, 4038 (doi:10.3390/rs15164038).

Trewin, D., Fisher, N., and Cressie, N. (2023). The Robodebt tragedy. Significance, 20, December 2023, 18-21 (doi:10.1093/jrssig/qmad092).


Cressie, N., Bertolacci, M., and Zammit-Mangion, A. (2022). From many to one: Consensus inference in a MIP. Geophysical Research Letters, 49, e2022GL098277 (doi:10.1029/2022GL098277).

Cressie, N., Sainsbury-Dale, M., and Zammit-Mangion, A. (2022). Basis-function models in spatial statistics. Annual Review of Statistics and its Application, 9, 373-400  (doi:10.1146/annurev-statistics-040120-020733).

Cressie, N., Pearse, A., and Gunawan, D. (2022). Optimal spatial prediction for non-negative spatial processes using a phi-divergence loss function, in Trends in Mathematical, Information, and Data Sciences, eds N. Balakrishnan, M. A. Gil, N. Martin, D. Morales, and M. Pardo. Springer Nature, Cham, CH, pp. 181-197   (doi:10.1007/978-3-031-04137-2_17).

Vu, Q., Zammit-Mangion, A., and Cressie, N. (2022). Modeling nonstationary and asymmetric multivariate spatial covariances via deformations. Statistica Sinica, 32, 2071-2093   (doi:10.5705/ss.202020.0156).

Zammit-Mangion, A., Bertolacci, M., Fisher, J., Stavert, A., Rigby, M., Cao, Y., and Cressie, N. (2022). WOMBAT v1.0: a fully Bayesian global flux-inversion framework. Geoscientific Model Development, 15, 45-73 (doi:10.5194/gmd-15-45-2022).

Zhang, B., Li, F., Sang, H., and Cressie, N. (2022). Inferring changes in Arctic sea ice through a spatio-temporal logistic autoregression fitted to remote-sensing data. Remote Sensing, 14, 5995 (doi:10.3390/rs14235995).


Cressie, N. (2021). A few statistical principles for data scienceAustralian & New Zealand Journal of Statistics, 63, 182-200 (doi:10.1111/anzs.12324).

Cressie, N. and Wikle, C. K. (2021). Modeling dependence in spatio-temporal econometrics, in Advances in Contemporary Statistics and Econometrics, eds A. Daouia and A. Ruiz-Gazen, Springer, Cham, Ch, pp. 363-383 (doi:10.1007/978-3-030-73249-3_19).

Barkhordarian, A., Bowman, K. W., Cressie, N., Jewell, J., and Liu, J. (2021). Emergent constraints on tropical atmospheric aridity―carbon feedbacks and the future of carbon sequestration. Environmental Research Letters, 16, 114008 (doi: 10.1088/1748-9326/ac2ce8).

Huang, H.-C., Cressie, N., Zammit-Mangion, A., and Huang, G. (2021). False discovery rates to detect signals from incomplete spatially aggregated data. Journal of Computational and Graphical Statistics, 30, 1081-1094 (doi:10.1080/10618600.2021.1873144).

Zammit-Mangion, A. and Cressie, N. (2021). FRK: An R package for spatial and spatio-temporal prediction with large datasets. Journal of Statistical Software, 98(4), 1-42 (doi:10.18637/jss.v098.i04).


Cressie, N. and Suesse, T. (2020). Great expectations and even greater exceedances from spatially referenced data. Spatial Statistics37, 100420 (doi:10.1016/j.spasta.2020.100420).

Cressie, N. and Wikle, C.K. (2020). Measuring, mapping, and uncertainty quantification in the space-time cubeRevista Matemática Complutense33, 643-660 (doi:10.1007/s13163-020-00359-7).

Stough, T., Cressie, N., Kang, E. L., Michalak, A. M., and Sahr, K. (2020). Spatial analysis and visualization of global data on multi-resolution hexagonal gridsJapanese Journal of Statistics and Data Science3, 107-128.

Zhang, B. and Cressie, N. (2020). Bayesian spatio-temporal modeling of Arctic sea ice extentBayesian Analysis15, 605-631.


Cressie, N. and Hardouin, C. (2019). A diagonally weighted matrix norm between two covariance matricesSpatial Statistics, 29, 316-328.

Nguyen, H., Cressie, N., and Hobbs, J. (2019). Sensitivity of Optimal Estimation satellite retrievals to misspecification of the prior mean and covariance, with application to OCO-2 retrievalsRemote Sensing11, 2770.

Weinberg, D., et al. (16 co-authors, including Cressie, N.) (2019). Effects of a government-academic partnership: Has the NSF-Census Bureau Research Network helped improve the U.S. statistical system? Journal of Survey Statistics and Methodology7, 589-619.

Zhang, B. and Cressie, N. (2019). Estimating spatial changes over time of Arctic sea ice using hidden 2 x 2 tables. Journal of Time Series Analysis40, 288-311.

Zhang, B., Cressie, N., and Wunch, D. (2019). Inference for errors-in-variables models in the presence of systematic errors with an application to a satellite remote sensing campaign. Technometrics61, 187-201.


Cressie, N. (2018). Mission CO2ntrol: A statistical scientist’s role in remote sensing of atmospheric carbon dioxide (with discussion). Journal of the American Statistical Association113, 152-181.
Supplemental Material for “Mission CO2ntrol: A statistical scientist's role in remote sensing of atmospheric carbon dioxide” by Noel Cressie, in Journal of the American Statistical Association113, 152-181 (2018).

Cressie, N. (2018). A statistical analysis of the Jacobian in retrievals of satellite data, in Handbook of Mathematical Geosciences: Fifty Years of IAMG, eds B.S. Daya Sagar, Q. Cheng, and F.P. Agterberg. Springer, Berlin, DE, 117-130. 

Bowman, K. W., Cressie, N., Qu, X., and Hall, A. (2018). A hierarchical statistical framework for emergent constraints: Application to snow-albedo feedbackGeophysical Research Letters45, 13,050-13,059.

Hardouin, C. and Cressie, N. (2018). Two-scale spatial models for binary dataStatistical Methods and Applications27, 1-24.

Marchetti, Y., Nguyen, H., Braverman, A., and Cressie, N. (2018). Spatial data compression via adaptive dispersion clusteringComputational Statistics and Data Analysis117, 138-153.

Zammit-Mangion, A., Cressie, N., and Shumack, C. (2018). On statistical approaches to generate Level 3 products from remote sensing retrievalsRemote Sensing10, 155.


Cressie, N., Burden, S., Shumack, C., Zammit-Mangion, A., and Zhang, B. (2017). Environmental InformaticsWiley StatsRef: Statistics Reference Online, pp. 1-8 (doi:10.1002/9781118445112.stat07717.pub2).

Cressie, N., Wang, R., and Maloney, B. (2017). The Atmospheric Infrared Sounder (AIRS) retrieval, revisitedIEEE Geosciences and Remote Sensing Letters14, 1504-1507.

Braverman, A., Chatterjee, S., Heyman, M., and Cressie, N. (2017). Probabilistic evaluation of competing climate modelsAdvances in Statistical Climatology, Meteorology and Oceanography3, 93-105.

Hobbs, J., Braverman, A., Cressie, N., Granat, R., and Gunson, M. (2017). Simulation-based uncertainty quantification for estimating atmospheric CO2 from satellite dataSIAM/ASA Journal on Uncertainty Quantification5, 956-985.

Nguyen, H., Cressie, N., and Braverman, A. (2017). Multivariate spatial data fusion for very large remote sensing dataRemote Sensing9, 142 (doi:10.3390/rs9020142).

Sayre, R., et al. (16 co-authors, including Cressie, N.). (2017). A three-dimensional mapping of the ocean based on environmental data. Oceanography30, 90-103 (doi:10.5670/oceanog.2017.116).

Zhang, B., Cressie, N., and Wunch, D. (2017). Statistical properties of atmospheric greenhouse gas measurements looking down from space and looking up from the groundChemometrics and Intelligent Laboratory Systems162, 214-222.


Cressie, N. and Kang, E. L. (2016). Hot enough for you? A spatial exploratory and inferential analysis of North American climate-change projectionsMathematical Geosciences48, 107-121 (doi:10.1007/s11004-015-9607-9).

Cressie, N., Wang, R., Smyth, M., and Miller, C.E. (2016). Statistical bias and variance for the regularized inverse problem: Application to space-based atmospheric CO2 retrievalsJournal of Geophysical Research: Atmospheres121, 5526-5537 (doi:10.1002/2015JDO24353).

Cressie, N. and Zammit-Mangion, A. (2016). Multivariate spatial covariance models: A conditional approachBiometrika103, 4, 915-935.

Bradley, J.R., Cressie, N., and Shi, T. (2016). A comparison of spatial predictors when datasets could be very largeStatistics Surveys10, 100-131.

Davies, G. and Cressie, N. (2016). Analysis of variability of tropical Pacific sea surface temperaturesAdvances in Statistical Climatology, Meteorology and Oceanography2, 155-169.

Sengupta, A., Cressie, N., Kahn, B. H., and Frey, R. (2016). Predictive inference for big, spatial, non-Gaussian data: MODIS cloud data and its change-of-supportAustralian and New Zealand Journal of Statistics58, 15-45.

Zammit-Mangion, A., Cressie, N., and Ganesan, A.L. (2016). Non-Gaussian bivariate modelling with application to atmosphere trace-gas inversionSpatial Statistics18, 194-220.


Cressie, N. and Burden, S. (2015). Figures of merit for simultaneous inference and comparisons in simulation experimentsStat4, 196-211.

Cressie, N. and Burden, S. (2015). Evaluation of diagnostics for hierarchical spatial statistical models, in Geometry Driven Statistics, eds I.L. Dryden and J.T. Kent. Wiley, Chichester, UK, pp. 241-259.

Bradley, J.R., Cressie, N., and Shi, T. (2015). Comparing and selecting spatial predictors using local criteria (with discussion)Test24, 1-28. (Rejoinder: 2015, Vol. 24, pp. 54-60.)

Burden, S., Cressie, N., and Steel, D. G. (2015). The SAR model for very large datasets: A reduced-rank approachEconometrics3, 317-338.

Zammit-Mangion, A., Cressie, N., Ganesan, A. L., O'Doherty, S., and Manning, A. J. (2015). Spatio-temporal bivariate statistical models for atmospheric trace-gas inversion. Chemometrics and Intelligent Laboratory Systems149, 227-241 (doi:10.1016/j.chemolab.2015.09.006).


Cressie, N. (2014). Environmental informatics: Uncertainty quantification in the environmental sciences, in Past, Present, and Future of Statistical Science, eds X. Lin, D.L. Banks, C. Genest, G. Molenberghs, D.W. Scott, and J-L Wang. CRC Press, Boca Raton, FL, 429-449.

Clifford, D., Pagendam, D., Baldock, J., Cressie, N., Farquharson, R., Farrell, M., MacDonald, L., and Murray, L. (2014). Re-thinking soil carbon modelling: A stochastic approach to quantify uncertaintiesEnvironmetrics25, 265-278.

Nguyen, H., Katzfuss, M., Cressie, N., and Braverman, A. (2014). Spatio-temporal data fusion for very large remote sensing datasetsTechnometrics56, 174-185.

Porter, A. T., Holan, S. H., Wikle, C. K., and Cressie, N. (2014). Spatial Fay-Herriot models for small area estimation with functional covariatesSpatial Statistics10, 27-42.

Zhuang, L. and Cressie, N. (2014). Bayesian hierarchical statistical SIRS modelsStatistical Methods and Applications23, 601-646.


Cressie, N. and Liu, D. (2013). Geographic Information Systems (GISs), spatial statistics in. Entry in Encyclopedia of Environmetrics, second edition, eds A.H. El-Shaarawi and W.W. Piegorsch. Wiley, Chichester, UK (4 pp.)

Cressie, N., Morara, M., Buxton, B., McMillan, N., Strauss, W., and Wilson, N. (2013). A Bayesian multivariate analysis of children's exposure to pesticidesEnvironmetrics24, 357-366.

Cressie, N. and Wang, R. (2013). Statistical properties of the state obtained by solving a nonlinear multivariate inverse problemApplied Stochastic Models in Business and Industry29, 424-438.

Box, J.E., Cressie, N., Bromwich, D. H., Jung, J-H., van den Broeke, M., Van Angelen, J. H., Forster, R., Miège, C., Mosley-Thompson, E., Vinther, B., and McConnell, J. R. (2013). Greenland ice sheet mass balance reconstruction. Part I: net snow accumulation (1600-2009)Journal of Climate25, 3919-3934.

Clifford, D., Cressie, N., England, J. R., Roxburgh, S. H., and Paul, K. I. (2013). Unbiased, efficient estimation and prediction of biomass from log-log allometric modelsForest Ecology Management310, 375-381.

Kang, E. L. and Cressie, N. (2013). Bayesian hierarchical ANOVA of regional climate-change projections from NARCCAP Phase IIInternational Journal of Applied Earth Observation and Geoinformation22, 3-15.

Parslow, J., Cressie, N., Campbell, E., Jones, E., and Murray, L. (2013). Bayesian learning and predictability in a stochastic nonlinear dynamical modelEcological Applications23, 679-698.

Sengupta, A. and Cressie, N. (2013). Empirical hierarchical modeling for count data using the Spatial Random Effects modelSpatial Economic Analysis8, 389-418.

Sengupta, A. and Cressie, N. (2013). Hierarchical statistical modeling of big spatial datasets using the exponential family of distributionsSpatial Statistics4, 14-44.

Zhuang, L., Cressie, N., Pomeroy, L., and Janies, D. (2013). Multi-species SIR models from a dynamical Bayesian perspectiveTheoretical Ecology6, 457-473.


Cressie, N. (2012). Spatio-temporal statistics in Earth sciences, in Water Information Research and Development Alliance (WIRADA) Science Symposium Proceedings, Melbourne, Australia, 1-5 August 2011, 323-329.

Cressie, N., Assunção, R., Holan, S. H., Levine, M., Nicolis, O., Zhang, J., and Zhou, J. (2012). Dynamical random-set modeling of concentrated precipitation in North AmericaStatistics and its Interface5, 169-181.

Kang, E. L., Cressie, N., and Sain, S. (2012). Combining outputs from the North American Regional Climate Change Assessment Program by using a Bayesian hierarchical modelJournal of the Royal Statistical Society, Series C (Applied Statistics)61, 291-313.

Katzfuss, M. and Cressie, N. (2012). Bayesian hierarchical spatio-temporal smoothing for very large datasetsEnvironmetrics23, 94-107.

Li, H., Calder, C.A., and Cressie, N. (2012). One-step estimation of spatial dependence parameters: Properties and extensions of the APLE statisticJournal of Multivariate Analysis105, 68-84.

Nguyen, H., Cressie, N., and Braverman, A. (2012). Spatial statistical data fusion for remote-sensing applicationsJournal of the American Statistical Association107, 1004-1018.

Zhuang, L. and Cressie, N. (2012). Spatio-temporal modeling of Sudden Infant Death Syndrome dataStatistical Methodology9, 117-143.


Cressie, N. and Medak, F.M. (2011). Using power-divergence statistics to test for homogeneity in product-multinomial distributions, in Modern Mathematical Tools and Techniques in Computing Complexity, eds L. Pardo, N. Balakrishnan, and M.A. Gil. Springer-Verlag, Berlin, DE, 157-169.

Braverman, A., Cressie, N., and Teixeira, J. (2011). A likelihood-based comparison of temporal models for physical processes. Statistical Analysis and Data Mining4, 247-258 (doi:10.1002/sam.10113).

Huang, C., Hsing, T., and Cressie, N. (2011). Nonparametric estimation of the variogram and its spectrumBiometrika98, 775-789.

Huang, C., Hsing, T., and Cressie, N. (2011). Spectral density estimation through a regularized inverse problemStatistica Sinica21, 1115-1124.

Kang, E.L. and Cressie, N. (2011). Bayesian inference for the Spatial Random Effects model. Journal of the American Statistical Association106, 972-983 (doi:10.1198/jasa.2011.tm09680).

Katzfuss, M. and Cressie, N. (2011). Spatio-temporal smoothing and EM estimation for massive remote-sensing data sets. Journal of Time Series Analysis32, 430-446 (doi:10.1111/j.1467-9892.2011.00732.x).

Paul, R. and Cressie, N. (2011). Lognormal block kriging for contaminated soilEuropean Journal of Soil Science62, 337-345.

Sain, S., Furrer, R., and Cressie, N. (2011). A spatial analysis of multivariate output from regional climate modelsAnnals of Applied Statistics5, 150-175.

Wunch, D., et al. (42 co-authors, including Cressie, N.). (2011). A method for evaluating bias in global measurements of CO2 total columns from spaceAtmospheric Chemistry and Physics11, 12317-12337.


Cressie, N. and Kang, E. L. (2010). High-resolution digital soil mapping: Kriging for very large datasets, in Proximal Soil Sensing, eds R.A. Viscarra Rossel, A. B. McBratney, and B. Minasny. Springer, Dordrecht, NL, 49-63.

Cressie, N., Shi, T., and Kang, E. L. (2010). Fixed rank filtering for spatio-temporal dataJournal of Computational and Graphical Statistics19, 724-745.

Ahlqvist, O., Ban, H., Cressie, N., and Zuniga-Shaw, N. (2010). Statistical counterpoint: Knowledge discovery of choreographic information using spatio-temporal analysis and visualizationApplied Geography30, 548-560.

Huang, C., Hsing, T., Cressie, N., Ganguly, A. R., Protopopescu, V. A., and Rao, N. S. (2010). Bayesian source detection and parameter estimation of a plume model based on sensor network measurements (with discussions). Applied Stochastic Models in Business and Industry26, 331-361 (doi:10.1002/asmb.859).

Kang, E.L., Cressie, N., and Shi, T. (2010). Using temporal variability to improve spatial mapping with application to satellite dataCanadian Journal of Statistics38, 271-289.


Cressie, N., Calder, C. A., Clark, J. S., Ver Hoef, J. M., and Wikle, C. K. (2009). Accounting for uncertainty in ecological analysis: The strengths and limitations of hierarchical statistical modeling (with discussion)Ecological Applications19, 553-570.

Calder, C. A. and Cressie, N. (2009). Kriging and variogram models, in International Encyclopedia of Human Geography, Vol. 1, eds R. Kitchin and N. Thrift. Elsevier, Oxford, UK, 49-55.

Craigmile, P. F., Calder, C. A., Li, H., Paul, R., and Cressie, N. (2009). Hierarchical model building, fitting, and checking: A behind-the-scenes look at a Bayesian analysis of arsenic exposure pathways (with discussion)Bayesian Analysis4, 1-62.

Huang, C., Yao, Y., Cressie, N., and Hsing, T. (2009). Multivariate intrinsic random functions for cokrigingMathematical Geosciences41, 887-904.

Kang, E. L., Liu, D., and Cressie, N. (2009). Statistical analysis of small-area data based on independence, spatial, non-hierarchical, and hierarchical modelsComputational Statistics and Data Analysis53, 3016-3032.


Cressie, N. and Johannesson, G. (2008). Fixed rank kriging for very large spatial data sets. Journal of the Royal Statistical Society, Series B70, 209-226 (doi:10.1111/j.1467-9868.2007.00633.x)

Cressie, N. and Kapat, P. (2008). Some diagnostics for Markov random fieldsJournal of Computational and Graphical Statistics17, 726-749.

Cressie, N. and Verzelen, N. (2008). Conditional-mean least-squares fitting of Gaussian Markov random fields to Gaussian fieldsComputational Statistics and Data Analysis52, 2794-2807.

Berliner, L. M., Cressie, N., Jezek, K., Kim, Y., Lam, C. Q., and van der Veen, C. J. (2008). Equilibrium dynamics of ice streams: A Bayesian statistical analysisStatistical Methods and Applications17, 145-165.

Berliner, L. M., Jezek, K., Cressie, N., Kim, Y., Lam, C. Q., and van der Veen, C. J. (2008). Modeling dynamic controls on ice streams: A Bayesian statistical approachJournal of Glaciology54, 705-714.

Pavlicova, M., Santner, T.J., and Cressie, N. (2008). Detecting signals in FMRI data using powerful FDR proceduresStatistics and its Interface1, 23-32.

Zhang, J., Craigmile, P.F., and Cressie, N. (2008). Loss function approaches to predict a spatial quantile and its exceedance regionTechnometrics50, 216-227.


Cressie, N., Buxton, B. E., Calder, C. A., Craigmile, P. F., Dong, C., McMillan, N. J., Morara, M., Santner, T. J., Wang, K., Young, G., and Zhang, J. (2007). From sources to biomarkers: A Bayesian approach to human exposure modeling. Journal of Statistical Planning and Inference137, 3361-3379 (doi:10.1016/j.jspi.2007.03.017).

Johannesson, G., Cressie, N., and Huang, H.-C. (2007). Dynamic multi-resolution spatial modelsEnvironmental and Ecological Statistics14, 5-25.

Li, H., Calder, C. A., and Cressie, N. (2007). Beyond Moran's I: Testing for spatial dependence based on the spatial autoregressive model. Geographical Analysis39, 357-375.

Sain, S. and Cressie, N. (2007). A spatial model for multivariate lattice dataJournal of Econometrics140, 226-259.

Shi, T. and Cressie, N. (2007). Global statistical analysis of MISR aerosol data: A massive data product from NASA's Terra satelliteEnvironmetrics18, 665-680.


Cressie, N. (2006). Block kriging for lognormal spatial processesMathematical Geology38, 413-443.

Cressie, N., Frey, J., Harch, B., and Smith, M. (2006). Spatial prediction on a river network. Journal of Agricultural, Biological, and Environmental Statistics11, 127-150 (doi:10.1198/108571106X110649).

Cressie, N., Perrin, O., and Thomas-Agnan, C. (2006). Doctors' prescribing patterns in the Midi-Pyrénées region of France: Point-process aggregation, in Case Studies in Spatial Point Process Modeling, eds A. Baddeley, P. Gregori, J. Mateu, R. Stoica, and D. Stoyan. Springer Lecture Notes in Statistics, No. 185, Springer, New York, NY, 183-195.

Craigmile, P. F., Cressie, N., Santner, T. J., and Rao, Y. (2006). A loss function approach to identifying environmental exceedancesExtremes8, 143-159.

Kornak, J., Irwin, M. E., and Cressie, N. (2006). Spatial point process models of defensive strategies: Detecting changesStatistical Inference for Stochastic Processes9, 31-46.

Pavlicova, M., Cressie, N., and Santner, T. J. (2006). Testing for activation in data from FMRI experimentsJournal of Data Science4, 275-289.


Cressie, N. and Pavlicova, M. (2005). Lognormal kriging: Bias adjustment and kriging variances, in Geostatistics Banff 2004: Proceedings of the Seventh International Geostatistics Congress, eds O. Leuangthong and C. V. Deutsch. Springer, Dordrecht, NL, 1027-1036.

Cressie, N., Perrin, O., and Thomas-Agnan, C. (2005). Likelihood-based estimation for Gaussian MRFsStatistical Methodology2, 1-16.

Cressie, N., Zhang, J., and Craigmile, P. F. (2005). Geostatistical prediction of spatial extremes and their extent, in Geostatistics for Environmental ApplicationsProceedings of the Fifth Conference on Geostatistics for Environmental Applications, eds P. Renard, H. Demougeot-Renard, and R. Froidevaux. Springer, Berlin, DE, 27-37.

Tzeng, S., Huang, H.-C., and Cressie, N. (2005). A fast, optimal spatial-prediction method for massive datasetsJournal of the American Statistical Association100, 1343-1357.


Cressie, N., Richardson, S., and Jaussent, I. (2004). Ecological bias: Use of maximum-entropy approximationsAustralian and New Zealand Journal of Statistics46, 233-255.

Johannesson, G. and Cressie, N. (2004). Finding large-scale spatial trends in massive, global, environmental datasetsEnvironmetrics15, 1-44.

Johannesson, G. and Cressie, N. (2004). Variance-covariance modeling and estimation for multi-resolution spatial models, in geoENV 2002 - Geostatistics for Environmental Applications, eds X. Sanchez-Vila, J. Carrera, and J. Gomez-Hernandez. Kluwer, Dordrecht, NL, 319-330.

Ver Hoef, J. M., Cressie, N., and Barry, R. P. (2004). Flexible spatial models based on the Fast Fourier Transform (FFT) for cokriging. Journal of Computational and Graphical Statistics13, 265-282 (doi:10.1198/1061860043498).

Wendt, D. A., Irwin, M. E., and Cressie, N. (2004). Waypoint analysis for command and controlNaval Research Logistics51, 1045-1067.


Cressie, N. and Kornak, J. (2003). Spatial statistics in the presence of location error with an application to remote sensing of the environmentStatistical Science18, 436-456.

Cressie, N., Pardo, L., and Pardo, M. (2003). Size and power considerations for testing loglinear models using Φ-divergence test statisticsStatistica Sinica13, 555-570.

Aldworth, J. and Cressie, N. (2003). Prediction of nonlinear spatial functionalsJournal of Statistical Planning and Inference112, 3-41.

Frey, J. and Cressie, N. (2003). Some results on constrained Bayes estimatorsStatistics and Probability Letters65, 389-399.

Hrafnkelsson, B. and Cressie, N. (2003). Hierarchical modeling of count data with application to nuclear fall-outEnvironmental and Ecological Statistics10, 179-200.

Wright, D. L., Stern, H. S., and Cressie, N. (2003). Loss functions for estimation of extrema with an application to disease mappingCanadian Journal of Statistics31, 251-266.


Cressie, N. (2002). Geographic Information Systems (GIS), spatial statistics in. Entry in Encyclopedia of Environmetrics, Vol. 2, eds A. H. El-Shaarawi and W. W. Piegorsch. Wiley, New York, NY, 894-897.

Cressie, N. (2002). Spatial statistics in environmental epidemiology. Entry in Encyclopedia of Environmetrics, Vol. 4, eds A. H. El-Shaarawi and W. W. Piegorsch. Wiley, New York, NY, 2076-2080.

Cressie, N. (2002). Variogram. Entry in Encyclopedia of Environmetrics, Vol. 4, eds A. H. El-Shaarawi and W. W. Piegorsch. Wiley, New York, NY, 2313-2316.

Cressie, N. (2002). Variogram estimation. Entry in Encyclopedia of Environmetrics, Vol. 4, eds A. H. El-Shaarawi and W. W. Piegorsch. Wiley, New York, NY, 2316-2321 (doi:10.1002/9780470057339.vav002m).

Cressie, N. and Pardo, L. (2002). Model checking in loglinear models using Φ-divergences and MLEsJournal of Statistical Planning and Inference103, 437-453.

Cressie, N. and Pardo, L. (2002). Phi-divergence statistic. Entry in Encyclopedia of Environmetrics, Vol. 3, eds A. H. El-Shaarawi and W. W. Piegorsch. Wiley, New York, 1551-1555.

Cressie, N. and Pavlicova, M. (2002). Calibrated spatial moving average simulationsStatistical Modelling2, 267-279.

Cressie, N. and Wikle, C. K. (2002). Space-time Kalman filter. Entry in Encyclopedia of Environmetrics, Vol. 4, eds A. H. El-Shaarawi and W. W. Piegorsch. Wiley, New York, NY, 2045-2049.

Gabrosek, J. and Cressie, N. (2002). The effect on attribute prediction of location uncertainty in spatial dataGeographical Analysis34, 262-285.

Huang, H. C., Cressie, N., and Gabrosek, J. (2002). Fast, resolution-consistent spatial prediction of global processes from satellite dataJournal of Computational and Graphical Statistics11, 63-88.

Irwin, M. E., Cressie, N., and Johannesson, G. (2002). Spatial-temporal nonlinear filtering based on hierarchical statistical models (with discussion)Test11, 249-302. (Corrigenda: 2003, Vol. 12, p. 279.)

Kaiser, M.S., Cressie, N., and Lee, J. (2002). Spatial mixture models based on exponential family conditional distributionsStatistica Sinica12, 449-474.

Lahiri, S.N., Lee, Y., and Cressie, N. (2002). On asymptotic distribution and asymptotic efficiency of least squares estimators of spatial variogram parametersJournal of Statistical Planning and Inference103, 65-85.

Mugglin, A. S., Cressie, N., and Gemmell, I. (2002). Hierarchical statistical modelling of influenza-epidemic dynamics in space and timeStatistics in Medicine21, 2703-2721.

Shen, X., Huang, H. C., and Cressie, N. (2002). Nonparametric hypothesis testing for a spatial signalJournal of the American Statistical Association97, 1122-1140. (Correction: 2005, Vol. 100, pp. 716-718.)

Zhu, J., Lahiri, S. N., and Cressie, N. (2002). Asymptotic inference for spatial CDFs over timeStatistica Sinica12, 843-861.


Cressie, N. and Collins, L. B. (2001). Analysis of spatial point patterns using bundles of product density LISA functionsJournal of Agricultural, Biological, and Environmental Statistics6, 118-135.

Cressie, N. and Collins, L. B. (2001). Patterns in spatial point locations: Local indicators of spatial association in a minefield with clutterNaval Research Logistics38, 333-347.

Cressie, N. and Johannesson, G. (2001). Kriging for cut-offs and other difficult problems, in geoENV III - Geostatistics for Environmental Applications, eds P. Monestiez, D. Allard, and R. Froidevaux. Kluwer, Dordrecht, NL, 299-310.

Cressie, N. and Liu, C. (2001). Binary Markov mesh models and symmetric Markov random fields: Some results on their equivalenceMethodology and Computing in Applied Probability3, 5-34.

Daniels, M. J. and Cressie, N. (2001). A hierarchical approach to covariance-function estimation for time seriesJournal of Time Series Analysis22, 253-266.

Huang, H. C. and Cressie, N. (2001). Multiscale graphical modeling in space: Applications to command and control, in Spatial Statistics: Methodological Aspects and Applications, ed. M. Moore. Springer Lecture Notes in Statistics, No. 159, Springer, New York, NY, 83-113.

Lee, J., Kaiser, M. S., and Cressie, N. (2001). Multiway dependence in exponential family conditional distributionsJournal of Multivariate Analysis79, 171-190.

Ver Hoef, J. M. and Cressie, N. (2001). Spatial statistics: Analysis of field experiments, in Design and Analysis of Ecological Experiments, 2nd edn, eds S. M. Scheiner and J. Gurevitch. Oxford University Press, New York, NY, 289-307.

Ver Hoef, J. M., Cressie, N., Fisher, R. N., and Case, T. J. (2001). Uncertainty and spatial linear models for ecological data, in Spatial Uncertainty for Ecology, eds C. Hunsaker, M. Goodchild, M. Friedl, and T. Case. Springer-Verlag, New York, NY, 214-237.

Zhu, J., Lahiri, S. N., and Cressie, N. (2001). Asymptotic distribution of the empirical cumulative distribution function predictor under nonstationarity, in Spatial Statistics: Methodological Aspects and Applications, ed. M. Moore. Springer Lecture Notes in Statistics, No. 159, Springer, New York, NY, 1-20.


Cressie, N. (2000). Geostatistical methods for mapping environmental exposures, in Spatial Epidemiology: Methods and Applications, eds P. Elliott, J.C. Wakefield, N.G. Best, and D.J. Briggs. Oxford University Press, Oxford, UK, 185-204.

Cressie, N. and Lawson, A. B. (2000). Hierarchical probability models and Bayesian analysis of mine locationsAdvances in Applied Probability32, 315-330.

Cressie, N. and Pardo, L. (2000). Minimum Φ-divergence estimator and hierarchical testing in loglinear modelsStatistica Sinica10, 867-884.

Cressie, N., Stern, H. S., and Wright, D. R. (2000). Mapping rates associated with polygonsJournal of Geographical Systems2, 61-69.

Cressie, N., Zhu, J., Baddeley, A. J., and Nair, M. G. (2000). Directed Markov point processes as limits of partially ordered Markov modelsMethodology and Computing in Applied Probability2, 5-21.

Berliner, L. M., Wikle, C. K., and Cressie, N. (2000). Long-lead prediction of Pacific SSTs via Bayesian dynamic modelingJournal of Climate13, 3953-3968.

Huang, H. C. and Cressie, N. (2000). Deterministic/stochastic wavelet decomposition for recovery of signal from noisy dataTechnometrics42, 262-276.

Huang, H. C. and Cressie, N. (2000). Asymptotic properties of maximum (composite) likelihood estimators for partially ordered Markov modelsStatistica Sinica10, 1325-1344.

Kaiser, M. S. and Cressie, N. (2000). The construction of multivariate distributions from Markov random fieldsJournal of Multivariate Analysis73, 199-220.

Lawson, A. B. and Cressie, N. (2000). Spatial statistical methods for environmental epidemiology, in Handbook of Statistics, Vol. 18: Bioenvironmental and Public Health Statistics, eds P.K. Sen and C.R. Rao. Elsevier, Amsterdam, NL, 357-396.

Stern, H. S. and Cressie, N. (2000). Posterior predictive model checks for disease mapping modelsStatistics in Medicine19, 2377-2397.

Wikle, C. K. and Cressie, N. (2000). Space-time statistical modeling of environmental data, in Quantifying Spatial Uncertainty in Natural Resources: Theory and Applications for GIS and Remote Sensing, eds H. T. Mowrer and R. G. Congalton. Ann Arbor Press, Chelsea, MI, 213-235.


Cressie, N. (1999). Statistical analysis of data from a Geographic Information System, in GIS en Waarachtig! Proceedings of Symposium Statistische Software 1999. Geodan, Amsterdam, NL, 21-36.

Cressie, N. and Huang, H. C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functionsJournal of the American Statistical Association94, 1330-1340. (Correction: 2001, Vol. 96, p. 784.)

Cressie, N., Kaiser, M. S., Daniels, M. J., Aldworth, J., Lee, J., Lahiri, S. N., and Cox, L. H. (1999). Spatial analysis of particulate matter in an urban environment, in geoENV II - Geostatistics for Environmental Applications, eds J. Gomez-Hernandez, A. Soares, and R. Froidevaux. Kluwer, Dordrecht, NL, 41-52.

Aldworth, J. and Cressie, N. (1999). Sampling designs and prediction methods for Gaussian spatial processes, in Multivariate Analysis, Design of Experiments, and Survey Sampling, ed. S. Ghosh. Marcel Dekker, New York, NY, 1-54.

Davidson, J., Cressie, N., and Hua, X. (1999). Texture synthesis and pattern recognition for partially ordered Markov modelsPattern Recognition32, 1475-1505.

Huang, H. C. and Cressie, N. (1999). Empirical Bayesian spatial prediction using wavelets, in Bayesian Inference in Wavelet Based Models, eds P. Mueller and B. Vidakovich. Springer Lecture Notes in Statistics, No. 141, Springer, New York, NY, 203-222.

Lahiri, S. N., Kaiser, M. S., Cressie, N., and Hsu, N. J. (1999). Prediction of spatial cumulative distribution functions using subsampling (with discussion and a rejoinder)Journal of the American Statistical Association94, 86-110.

Stern, H. S. and Cressie, N. (1999). Inference for extremes in disease mapping, in Disease Mapping and Risk Assessment for Public Health, eds A. Lawson et al. Wiley, Chichester, UK, 63-84.

Wikle, C. K. and Cressie, N. (1999). A dimension-reduced approach to space-time Kalman filteringBiometrika86, 815-829.


Cressie, N. (1998). Transect-spacing design of ice cores on the Antarctic continentCanadian Journal of Statistics26, 405-418.

Cressie, N. (1998). Aggregation and interaction issues in statistical modeling of spatio-temporal processesGeoderma85, 133-140.

Cressie, N. and Davidson, J. L. (1998). Image analysis with partially ordered Markov modelsComputational Statistics and Data Analysis29, 1-26.

Cressie, N. and Davidson, J. L. (1998). Image processing. Entry in Encyclopedia of Statistical Sciences, Update Vol. 2, eds S. Kotz, C.B. Read, and D.L. Banks. Wiley, New York, NY, 314-328. (Republished in 2009 in Methods and Applications of Statistics in the Life and Health Sciences, ed. N. Balakrishnan. Wiley, Hoboken, NJ, 397-414.)

Cressie, N. and Morgan, P. B. (1998). Variable-sample-size sequential probability ratio test (VPRT). Entry in Encyclopedia of Statistical Sciences, Update Vol. 2, eds S. Kotz, C.B. Read, and D. L. Banks. Wiley, New York, NY, 691-699.

Cressie, N. and Wikle, C. K. (1998). The variance-based cross-variogram: You can add apples and orangesMathematical Geology30, 789-799.

Wikle, C. K., Berliner, L. M., and Cressie, N. (1998). Hierarchical Bayesian space-time modelsEnvironmental and Ecological Statistics5, 117-154.


Cressie, N. (1997). Jackknifing in the presence of inhomogeneityTechnometrics39, 45-51.

Cressie, N. and Aldworth, J. (1997). Spatial statistical analysis and its consequences for spatial sampling, in Geostatistics Wollongong '96, Vol. 1, eds E.Y. Baafi and N. A. Schofield. Kluwer, Dordrecht, NL, 126-137.

Cressie, N. and Majure, J. J. (1997). Spatio-temporal statistical modeling of livestock waste in streamsJournal of Agricultural, Biological, and Environmental Statistics2, 24-47.

Cressie, N. and Majure, J. J. (1997). Non-point-source pollution of surface waters over a watershed, in Statistics for the Environment 3: Pollution Assessment and Control, eds V. Barnett and K.F. Turkman. Wiley, Chichester, UK, 201-224.

Carroll, S.S. and Cressie, N. (1997). Spatial modeling of snow water equivalent using covariances estimated from spatial and geomorphic attributesJournal of Hydrology190, 42-59.

Cook, D., Symanzik, J., Majure, J. J., and Cressie, N. (1997). Dynamic graphics in a GIS: More examples using linked softwareComputers and Geosciences23, 371-385.

Helterbrand, J. D. and Cressie, N. (1997). Object identification using Markov random field segmentation models at multiple resolutions of a rectangular lattice, in Modelling Longitudinal and Spatially Correlated Data: Methods, Applications, and Future Directions, eds T. Gregoire et al. Springer Lecture Notes in Statistics, No. 122, Springer, New York, NY, 159-173.

Kaiser, M. S. and Cressie, N. (1997). Modeling Poisson variables with positive spatial dependenceStatistics and Probability Letters35, 423-432.

Kaiser, M. S., Hsu, N. J., Cressie, N., and Lahiri, S. N. (1997). Inference for spatial processes using subsampling: A simulation studyEnvironmetrics8, 485-502.

Majure, J. J. and Cressie, N. (1997). Dynamic graphics for exploring spatial dependence in multivariate spatial dataGeographical Systems4, 131-158.

Morgan, P. B. and Cressie, N. (1997). A comparison of the cost-efficiencies of the sequential, group-sequential, and variable-sample-size-sequential probability ratio testsScandinavian Journal of Statistics24, 181-200.

Ver Hoef, J. M. and Cressie, N. (1997). Using hidden Markov chains and empirical Bayes change-point estimation for transect dataEnvironmental and Ecological Statistics4, 247-264.


Cressie, N. (1996). Change of support and the modifiable areal unit problemGeographical Systems3, 159-180.

Cressie, N. (1996). PIC: Power divergence information criterion, in Statistical Theory and Applications: Papers in Honor of Herbert A. David, eds H. N. Nagaraja, P. K. Sen, and D. F. Morrison. Springer, New York, NY, 3-14.

Cressie, N. (1996). Weighted jackknife variance estimation for functions of rates and proportions, in Research Developments in Probability and Statistics, eds E. Brunner and M. Denker. VSP International Science Publishers, Utrecht, NL, 343-352.

Cressie, N. and Hartfield, M. N. (1996). Conditionally specified Gaussian models for spatial statistical analysis of field trialsJournal of Agricultural, Biological, and Environmental Statistics1, 60-77.

Cressie, N. and Lahiri, S. N. (1996). Asymptotics for REML estimation of spatial covariance parametersJournal of Statistical Planning and Inference50, 327-341.

Carroll, S.S. and Cressie, N. (1996). A comparison of geostatistical techniques used to estimate snow water equivalentWater Resources Bulletin32, 267-278.

Cook, D., Majure, J.J., Symanzik, J., and Cressie, N. (1996). Dynamic graphics in a GIS: Exploring and analyzing multivariate spatial data using linked softwareComputational Statistics11, 467-480.

Huang, H.C. and Cressie, N. (1996). Spatio-temporal prediction of snow water equivalent using the Kalman filterComputational Statistics and Data Analysis22, 159-175.


Cressie, N. (1995). Bayesian smoothing of rates in small geographic areasJournal of Regional Science35, 659-673.

Cannon, A. and Cressie, N. (1995). Temporal analogues to spatial K functionsBiometrical Journal37, 351-373.

Carroll, S. S., Day, G. N., Cressie, N., and Carroll, T. R. (1995). Spatial modeling of snow water equivalent using airborne and ground-based snow dataEnvironmetrics6, 127-139.

Grondona, M. O. and Cressie, N. (1995). Residuals based estimators of the covariogramStatistics26, 209-218.

Helterbrand, J. D., Davidson, J. L., and Cressie, N. (1995). Optimal closed boundary identification in gray-scale imageryJournal of Mathematical Imaging and Vision5, 179-205.


Cressie, N. (1994). Models for spatial processes, in Statistical Methods for Physical Science, eds J. Stanford and S. Vardeman. Academic Press, New York, NY, 93-124.

Cressie, N. (1994). Spatial chemostatistics, in Environmental Statistics, Assessment and Forecasting, eds C. R. Cothern and N. P. Ross. Lewis Publishers, Boca Raton, FL, 131-146.

Cressie, N. and Biele, J. (1994). A sample-size optimal Bayesian procedure for sequential pharmaceutical trialsBiometrics50, 700-711.

Cressie, N., Biele, J., and Morgan, P. B. (1994). Sample-size-optimal sequential testingJournal of Statistical Planning and Inference39, 305-327.

Cressie, N. and Helterbrand, J. D. (1994). Multivariate spatial statistical modelsGeographical Systems1, 179-188.

Helterbrand, J. D. and Cressie, N. (1994). Universal cokriging under intrinsic coregionalizationMathematical Geology26, 205-226.

Helterbrand, J. D., Cressie, N., and Davidson, J. L. (1994). A statistical approach to identifying closed object boundaries in imagesAdvances in Applied Probability26, 831-854.

Rathbun, S. L. and Cressie, N. (1994). Asymptotic properties of estimators for the parameters of spatial inhomogeneous Poisson point processesAdvances in Applied Probability26, 122-154.

Rathbun, S. L. and Cressie, N. (1994). A space-time survival point process for a longleaf pine forest in southern GeorgiaJournal of the American Statistical Association89, 1164-1174.


Cressie, N. (1993). Aggregation in geostatistical problems, in Geostatistics Troia '92, Vol. 1, ed. A. Soares. Kluwer, Dordrecht, NL, 25-36.

Cressie, N. (1993). Regional mapping of incidence rates using spatial Bayesian modelsMedical Care31, YS60-YS65.

Cressie, N. (1993). Geostatistics: A tool for environmental modelers, in Environmental Modeling with GIS, eds M. F. Goodchild, B. O. Parks, and L. T. Steyaert. Oxford University Press, Oxford, UK, 414-421.

Cressie, N. and Lahiri, S. N. (1993). The asymptotic distribution of REML estimatorsJournal of Multivariate Analysis45, 217-233.

Cressie, N. and Morgan, P. B. (1993). The VPRT: A sequential testing procedure dominating the SPRTEconometric Theory9, 431-450.

Cressie, N. and Ver Hoef, J. (1993). Spatial statistical analysis of environmental and ecological data, in Environmental Modeling with GIS, eds M. F. Goodchild, B. O. Parks, and L. T. Steyaert. Oxford University Press, Oxford, UK, 404-413.

Gotway, C. and Cressie, N. (1993). Improved multivariate prediction under a general linear modelJournal of Multivariate Analysis45, 56-72.

Grondona, M. O. and Cressie, N. (1993). Efficiency of block designs under stationary second-order autoregressive errorsSankhya A55, 267-284.

Ver Hoef, J. M. and Cressie, N. (1993). Multivariable spatial predictionMathematical Geology25, 219-240. (Errata: 1994, Vol. 26, pp. 273-275.)

Ver Hoef, J. M. and Cressie, N. (1993). Spatial statistics: Analysis of field experiments, in Design and Analysis of Ecological Experiments, eds S. M. Scheiner and J. Gurevitch. Chapman and Hall, London, UK, 319-341.

Ver Hoef, J. M., Cressie, N., and Glenn-Lewin, D. C. (1993). Spatial models for spatial statistics: Some unificationJournal of Vegetation Science4, 441-452.


Cressie, N. (1992). Smoothing regional maps using empirical Bayes predictorsGeographical Analysis24, 75-95.

Cressie, N. (1992). REML estimation in empirical Bayes smoothing of census undercountSurvey Methodology18, 75-94.

Cressie, N. and Hulting, F. L. (1992). A spatial statistical analysis of tumor growthJournal of the American Statistical Association87, 272-283.

Cressie, N. and Lele, S. (1992). New models for Markov random fieldsJournal of Applied Probability29, 877-884.

Cressie, N. and Zimmerman, D. L. (1992). On the stability of the geostatistical methodMathematical Geology24, 45-59.

Zimmerman, D. L. and Cressie, N. (1992). Mean squared prediction error in the spatial linear model with estimated covariance parametersAnnals of the Institute of Statistical Mathematics44, 27-43.


Cressie, N. (1991). Geostatistical analysis of spatial data, in Spatial Statistics and Digital Image Analysis. National Academy Press, Washington, DC, 87-108.

Cressie, N. and Dajani, A. (1991). Empirical Bayes estimation of U. S. undercount based on artificial populationsJournal of Official Statistics7, 57-67.

Grondona, M. O. and Cressie, N. (1991). Using spatial considerations in the analysis of experimentsTechnometrics33, 381-392.

Medak, F. and Cressie, N. (1991). Confidence regions in ternary diagrams based on the power-divergence statisticsMathematical Geology23, 1045-1057.

Nanayakkara, N. and Cressie, N. (1991). Combining two unbiased estimators of a common mean of two normal populationsAustralian Journal of Statistics33, 43-56.

Nanayakkara, N. and Cressie, N. (1991). Robustness to unequal scale and other departures from the classical linear model, in Directions in Robust Statistics and Diagnostics, Part II, eds W. Stahel and S. Weisberg. IMA Volumes in Mathematics and its Applications, Vol. 34, Springer, New York, 65-113.


Cressie, N. (1990). The origins of krigingMathematical Geology22, 239-252.

Cressie, N., Gotway, C. A., and Grondona, M. O. (1990). Spatial prediction from networksChemometrics and Intelligent Laboratory Systems7, 251-271.

Gotway, C. and Cressie, N. (1990). A spatial analysis of variance applied to soil-water infiltrationWater Resources Research26, 2695-2703.


Cressie, N. (1989). The many faces of spatial prediction, in Geostatistics, Vol. 1, ed. M. Armstrong. Kluwer, Dordrecht, NL, 163-176.

Cressie, N. (1989). Ergodicity for time series and spatial processesJournal of Statistical Computation and Simulation32, 61-63.

Cressie, N. (1989). GeostatisticsAmerican Statistician43, 197-202.

Cressie, N. (1989). Empirical Bayes estimation of undercount in the Decennial CensusJournal of the American Statistical Association84, 1033-1044.

Cressie, N. and Chan, N. H. (1989). Spatial modeling of regional variablesJournal of the American Statistical Association84, 393-401.

Cressie, N. and Morgan, P. B. (1989). Design considerations for Neyman-Pearson and Wald hypothesis testingMetrika36, 317-325.

Cressie, N. and Read, T. R. C. (1989). Cressie-Read statistic, entry in Encyclopedia of Statistical Sciences, Supplement Volume, eds S. Kotz and N. L. Johnson. Wiley, New York, 37-39.

Cressie, N. and Read, T. R. C. (1989). Pearson's X2 and the loglikelihood ratio statistic G2: A comparative reviewInternational Statistical Review57, 19-43.

Cressie, N. and Read, T. R. C. (1989). Spatial data analysis of regional countsBiometrical Journal31, 699-719.

Ruppert, D., Cressie, N. A. C., and Carroll, R. J. (1989). A transformation weighting model for estimating Michaelis-Menten parametersBiometrics45, 637-656.


Cressie, N. (1988). Variogram, entry in Encyclopedia of Statistical Sciences, Vol. 9, eds S. Kotz and N. L. Johnson. Wiley, New York, 489-491.

Cressie, N. (1988). Spatial prediction and ordinary krigingMathematical Geology20, 405-421. (Erratum: 1989, Vol. 21, pp. 493-494.)

Cressie, N. (1988). A graphical procedure for determining nonstationarity in time seriesJournal of the American Statistical Association83, 1108-1116. (Correction: 1990, Vol. 85, p. 272.)

Cressie, N. (1988). When are census counts improved by adjustment? Survey Methodology14, 191-208.

Cressie, N. and Morgan, P. B. (1988). The VPRT: Optimal sequential and nonsequential testing, in Statistical Decision Theory and Related Topics IV, Vol. 2, eds S. S. Gupta and J. O. Berger. Springer, New York, 107-118.

Kernan, W. J., Mullenix, P. J., Kent, R., Hopper, D. L., and Cressie, N. A. C. (1988). Analysis of the time distribution and time sequence of behavioral actsInternational Journal of Neuroscience43, 35-51.


Cressie, N. (1987). A nonparametric view of generalized covariances for krigingMathematical Geology19, 425-449.

Cressie, N. (1987). Using the scan statistic to test for uniformity, in Goodness-of-FitColloquia Mathematica Societatis Janos Bolyai, Vol. 45, eds P. Revesz et al. North Holland, Amsterdam, NL, 87-100.

Cressie, N. and Laslett, G. M. (1987). Random set theory and problems of modelingSIAM Review29, 557-574.

Cressie, N. and Shaughnessy, P. (1987). Statistical methods for estimating numbers of Cape fur seal pups from aerial surveysMarine Mammal Science3, 297-307.

Cressie, N. A. C. and Horton, R. (1987). A robust-resistant spatial analysis of soil-water infiltrationWater Resources Research23, 911-917.


Cressie, N. (1986). Kriging nonstationary dataJournal of the American Statistical Association81, 625-634.

Cressie, N. and Borkent, M. (1986). The moment generating function has its momentsJournal of Statistical Planning and Inference13, 337-344.

Cressie, N. A. C. and Whitford, H. J. (1986). How to use the two sample t-testBiometrical Journal28, 131-148.

Cressie, N. A. C., Withers, R. T., and Craig, N. P. (1986). The statistical analysis of somatotype dataYearbook of Physical Anthropology29, 197-208.

Hamlett, J. M., Horton, R., and Cressie, N. A. C. (1986). Resistant and exploratory techniques for use in semivariogram analysesSoil Science Society of America Journal50, 868-875.


Cressie, N. (1985). Fitting variogram models by weighted least squaresJournal of the International Association for Mathematical Geology17, 563-586.

Cressie, N. (1985). When are relative variograms useful in geostatistics? Journal of the International Association for Mathematical Geology17, 693-702.

Cressie, N. and Read, T. R. C. (1985). Do sudden infant deaths come in clustersStatistics and Decisions, Supplement Issue 2, 333-349.

Cressie, N. and Seheult, A. (1985). Empirical Bayes estimation in sampling inspectionBiometrika72, 451-458.


Cressie, N. (1984). Towards resistant geostatistics, in Geostatistics for Natural Resources Characterization, Part 1, eds G. Verly et al. Reidel, Dordrecht, NL, 21-44.

Cressie, N. and Glonek, G. (1984). Median based covariogram estimators reduce biasStatistics and Probability Letters2, 299-304.

Cressie, N. and Read, T. R. C. (1984). Multinomial goodness-of-fit testsJournal of the Royal Statistical Society, Series B46, 440-464.

Cressie, N. A. C., Sheffield, L. J., and Whitford, H. J. (1984). Use of the one sample t-test in the real worldJournal of Chronic Diseases37, 107-114.

Hawkins, D. M. and Cressie, N. (1984). Robust kriging - a proposalJournal of the International Association for Mathematical Geology16, 3-18.


Cressie, N. (1983). Solving extrema problems in statistics by weighted sumsThe Mathematical Scientist8, 103-113.

Cressie, N. and Holland, P. W. (1983). Characterizing the manifest probabilities of latent trait modelsPsychometrika48, 129-141.

Keightley, D. D., Fisher, R. J., and Cressie, N. A. C. (1983). Properties and interpretation of the Woolf and Scatchard plots in analysing data from steroid receptor assaysJournal of Steroid Biochemistry19, 1407-1412.


Cressie, N. (1982). A useful empirical Bayes identityAnnals of Statistics10, 625-629.

Cressie, N. (1982). Playing safe with misweighted meansJournal of the American Statistical Association77, 754-759.

Cressie, N. (1982). Empirical Bayes estimation for discrete distributionsSouth African Statistical Journal16, 25-37.


Cressie, N. (1981). Transformations and the jackknifeJournal of the Royal Statistical Society, Series B43, 177-182.

Cressie, N. and Davis, R. W. (1981). The supremum distribution of another Gaussian processJournal of Applied Probability18, 131-138.

Cressie, N., Davis, A. S., Folks, J. L., and Policello, G. E. II. (1981). The moment-generating function and negative integer momentsAmerican Statistician35, 148-150.

Cressie, N. A. C. and Keightley, D. D. (1981). Analysing data from hormone-receptor assaysBiometrics37, 235-249.


Cressie, N. (1980). Relaxing assumptions in the one sample t-testAustralian Journal of Statistics22, 143-153.

Cressie, N. (1980). M-estimation in the presence of unequal scaleStatistica Neerlandica34, 19-32.

Cressie, N. (1980). The asymptotic distribution of the scan statistic under uniformityAnnals of Probability8, 828-840.

Cressie, N. and Hawkins, D. M. (1980). Robust estimation of the variogram: I. Journal of the International Association for Mathematical Geology12, 115-125.

Keightley, D. D. and Cressie, N. A. C. (1980). The Woolf plot is more reliable than the Scatchard plot in analysing data from hormone receptor assaysJournal of Steroid Biochemistry13, 1317-1323.


Cressie, N. (1979). A central limit theorem for random setsZeitschrift fur Warhscheinlichkeitstheorie und verwandte Gebiete49, 37-47.

Cressie, N. (1979). An optimal statistic based on higher order gapsBiometrika66, 619-627.

Cressie, N. (1979). A quick and easy empirical Bayes estimate of true scoresSankhya B41, 101-108.

Cressie, N. A. C. and Keightley, D. D. (1979). The underlying structure of the direct linear plot with application to the analysis of hormone-receptor interactionsJournal of Steroid Biochemistry11, 1173-1180.


Cressie, N. (1978). A strong limit theorem for random setsAdvances in Applied Probability (Supplement)10, 36-46.

Cressie, N. (1978). Power results for tests based on high-order gapsBiometrika65, 214-218.

Cressie, N. (1978). The exponential and power data transformationsThe Statistician27, 57-60.

Cressie, N. (1978). Estimation of the integral of a stochastic processBulletin of the Australian Mathematical Society18, 83-93.

Cressie, N. (1978). A finely tuned continuity correctionAnnals of the Institute of Statistical Mathematics30, 435-442.

Cressie, N. (1978). Testing for the equality of two binomial proportionsAnnals of the Institute of Statistical Mathematics30, 421-427.

Cressie, N. A. C. (1978). Removing nonadditivity from two-way tables with one observation per cellBiometrics34, 505-513.


Cressie, N. (1977). On some properties of the scan statistic on the circle and the line. Journal of Applied Probability14, 272-283.

Cressie, N. (1977). The minimum of higher order gaps. Australian Journal of Statistics19, 132-143.


Cressie, N. (1976). On the logarithms of high-order spacingsBiometrika63, 343-355.


Cressie, N. (1975). A note on the behaviour of the stable distributions for small index αZeitschrift fur Wahrscheinlichkeitstheorie und verwandte Gebiete33, 61-64.

Lord, F. M. and Cressie, N. (1975). An empirical Bayes procedure for finding an interval estimateSankhya B37, 1-9.


Cressie, N. (1974). A two-dimensional random walk in the presence of a partially reflecting barrierJournal of Applied Probability11, 199-205.


Unrefereed Articles


Cressie, N., Bertolacci, M., and Zammit-Mangion, A. (2022). Spatio-temporal prediction of global carbon-dioxide fluxes at Earth’s surface using the fully Bayesian WOMBAT framework, in METMA X Proceedings of the 10th International Workshop on Spatio-Temporal Modelling (doi:10.21001/METMA_X).

Cressie, N., Jacobson, J., and Bertolacci, M. (2022). Release of Web-Project: Global CO2 Flux, showing CO2 flux inversions obtained using the fully Bayesian WOMBAT framework.


Cressie, N., Mannshardt, E., and Kang, E. L. (2012). Release of Web-Project: Warming, showing projected temperature increases in North America in the period 2041-2070.

Bradley, J.R., Cressie, N., and Shi, T. (2012). Local spatial-predictor selection, in 2012 Proceedings of the Joint Statistical Meetings. American Statistical Association, Alexandra, VA, 3098-3110.

Sengupta, A., Cressie, N., Frey, R., and Kahn, B. (2012). Statistical modeling of MODIS cloud data using the Spatial Random Effects model, in 2012 Proceedings of the Joint Statistical Meetings. American Statistical Association, Alexandra, VA, 3111-3123.


Cressie, N., Hoeting, J. A., Lele, S., McRoberts, R., Ogle, K., Smith, R., Stefanski, L., and Ziv, G. (2011). Measuring, monitoring and forecasting progress toward sustainability, in Mathematical and Statistical Challenges for Sustainability: Report of a Workshop held November 15-17, 2010. (18 pp.) American Mathematical Society, Providence, RI, 102-118.

Cressie, N. and Katzfuss, M. (2011). Release of Web-Project: CO2, in combination with release of Tutorial on Fixed Rank Kriging of CO2 data, showing global spatial and spatio-temporal statistical modeling and mapping of CO2.

Bradley, J.R., Cressie, N., and Shi, T. (2011). Selection of rank and basis functions in the spatial random effects model, in 2011 Proceedings of the Joint Statistical Meetings. American Statistical Association, Alexandria, VA, 3393-3406.


Cressie, N. and Calder, C. A. (2010). Release of Web-Project: STB, showing statistical modeling and analysis of human-exposure pathways from sources to biomarkers.

Smith, R. and Cressie, N. (2010). Statistical interpolation methods; supplement to the White Paper, "Spatial and temporal interpolation of environmental data," written for the Workshop on Creating Surface Temperature Datasets to Meet 21st Century Challenges, Met Office Hadley Center, Exeter, UK, September 2010 (8 pp.)


Katzfuss, M. and Cressie, N. (2009). Maximum likelihood estimation of covariance parameters in the spatial-random-effects model, in 2009 Proceedings of the Joint Statistical Meetings. American Statistical Association, Alexandria, VA, 3378-3390.


Cressie, N. and Kang, L. (2008). Soil mapping using spatial statistics: Kriging for very large datasets, in Proceedings of First Global Workshop on High Resolution Digital Soil Sensing and Mapping, Vol. I, Sydney, Australia (14 pp.).


Calder, C.A. and Cressie, N. (2007). Some topics in convolution-based spatial modelingBulletin of the International Statistical Institute - LXII (Proceedings of the 56th Session of the International Statistical Institute, Lisbon, Portugal), 132-139.

Paul, R., Cressie, N., Buxton, B. E., Calder, C. A., Craigmile, P. F., Li, H., McMillan, N. J., Morara, M., Sanford, J., Santner, T. J., and Zhang, J. (2007). A Bayesian hierarchical model of arsenic exposure based on NHEXAS data: A comparison of US EPA Region 5 and Arizona, in 2007 Proceedings of the Joint Statistical Meetings. American Statistical Association, Alexandria, VA, 1055-1062.

Sain, S.R., Furrer, R., and Cressie, N. (2007). Combining regional climate model output via a multivariate Markov random field modelBulletin of the International Statistical Institute - LXII (Proceedings of the 56th Session of the International Statistical Institute, Lisbon, Portugal), 1375-1382.

Shi, T. and Cressie, N. (2007). Data mining of MISR aerosol product using spatial statisticsProceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining. IEEE Press, Piscataway, NJ, 712-719.


Cressie, N. and Johannesson, G. (2006). Spatial prediction for massive datasets, in Mastering the Data Explosion in the Earth and Environmental Sciences: Proceedings of the Australian Academy of Science Elizabeth and Frederick White Conference. Australian Academy of Science, Canberra, Australia (11 pp.).


Cressie, N. and Yao, Y. (2005). Release of Web-Project: TCO, showing spatial prediction of total column ozone over the globe using a fast multi-resolution spatial statistical model.

Cressie, N., Berliner, L. M., and Jezek, K. C. (2005). Release of Web-Project: Ice Streams, in combination with release of Tutorial on Bayesian Statistics for Geophysicists, showing physical-statistical modeling of ice-stream dynamics.

Berliner, L. M., Cressie, N., Jezek, K., Kim, Y., and Lam, C. Q. (2005). Hierarchical Bayesian modeling of the movement of ice streams, in Statistical Solutions to Modern Problems: Proceedings of the 20th International Workshop on Statistical Modelling, Sydney, Australia, July 10-15, 2005, eds A. R. Francis, K. M. Matawie, A. Oschlack, and G. K. Smyth, 3-15.

Ganguly, A. R., Hsing, T., Katz, R., Erickson, D. J., Ostrouchov, G., Wilbanks, T. J., and Cressie, N. (2005). Multivariate dependence among extremes, abrupt change, and anomalies in space and time for climate applications, in Proceedings of the International Workshop on Data Mining Methods for Anomaly Detection, eds D. Margineantu, S. Bay, P. Chan, and T. Lane, 25-26.


Cressie, N. and Irwin, M. (2004). Release of Web-Project: ENSO, showing long-lead forecasting of Tropical Pacific sea surface temperature anomalies.


Cressie, N., Wendt, D., Johannesson, G., Mugglin, A., and Hrafnkelsson, B. (2003). A spatial-temporal statistical approach to problems in command and control, in Proceedings of the Sixth Annual US Army Conference on Applied Statistics 2000, Army Research Laboratory, eds B. Bodt and E. Wegman, 170-190.

Johannesson, G., Cressie, N., and Huang, H.-C. (2003). Dynamic multi-resolution spatial models, in Proceedings of AIC2003: Science of Modeling, eds T. Higuchi, Y. Iba, and M. Ishiguro. Institute of Statistical Mathematics, Tokyo, Japan, 167-174.


Pavlicova, M., Cressie, N., and Santner, T. J. (2002). Using enhanced FDR for simultaneous thresholding of FMRI data, in 2002 Proceedings of the Joint Statistical Meetings, Biometrics Section. American Statistical Association, Alexandria, VA, 2653-2658.

Sain, S. and Cressie, N. (2002). Multivariate lattice models for spatial environmental data, in 2002 Proceedings of the Joint Statistical Meetings, Section on Statistics and the Environment. American Statistical Association, Alexandria, VA, 2820-2825.


Cressie, N. and Johannesson, G. (2001). Space-time modeling of total column ozone (TCO) satellite data: Exploratory analysis in a multiresolution context, in Proceedings of the First Spanish Workshop on Spatio-Temporal Modelling of Environmental Processes (METMA). Benicassim, Castellon, Spain, 41-49.

Cressie, N. and Ver Hoef, J. M. (2001). Multivariate geostatistics for precision agriculture (with discussion)Bulletin of the International Statistical Institute, Invited Papers Volume 59, Book 1, 407-410.

Wendt, D., Cressie, N., and Johannesson, G. (2001). A spatial-temporal statistical approach to command and control problems in battle-space digitization, in Battlespace Digitization and Network-Centric Warfare, ed. R. Suresh. Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 439. SPIE, Bellingham, WA, 232-243.


Cressie, N. (2000). Position paper: Workshop on Hierarchical Modeling in Environmental Statistics (Columbus, OH, May 14-16, 2000). Available at URL,

Cressie, N. (2000). Spatial statistics and environmental sciences, in 2000 Proceedings of the Section on Statistics and the Environment. American Statistical Association, Alexandria, VA, 1-10.

Cressie, N. and Mugglin, A. S. (2000). Spatio-temporal hierarchical modeling of an infectious disease from (simulated) count data, in Compstat. Proceedings in Computational Statistics, eds J. G. Bethlehem and P. G. M. van der Heijden. Physica-Verlag, Heidelberg, DE, 41-52.


Gabrosek, J., Cressie, N., and Huang, H. C. (1999). Spatio-temporal prediction of level 3 data for NASA's earth observing systems, in Spatial Accuracy Assessment: Land Information Uncertainty in Natural Resources, eds K. Lowell and A. Jaton. Ann Arbor Press, Chelsea, MI, 331-337.


Cressie, N. and Lawson, A. B. (1998). Bayesian hierarchical analysis of minefield data, in Detection and Remediation Technologies for Mines and Minelike Targets III, eds A.C. Dubey, J.F. Harvey, and J.T. Broach. Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 3392. SPIE, Bellingham, WA, 930-940.


Cressie, N. and Lawson, A. B. (1997). Models and inference for clustering of locations of mines and minelike objects, in Detection and Remediation Technologies for Mines and Minelike Targets II, eds A.C. Dubey and R.L. Barnard. Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 3079. SPIE, Bellingham, WA, 519-530.

Aldworth, J. and Cressie, N. (1997). Comparison of spatial cumulative distribution function predictors of a spatial process sampled with measurement error, in 1997 Proceedings of the Section on Statistics and the Environment. American Statistical Association, Alexandria, VA, 43-48.

Hua, X., Davidson, J.L., and Cressie, N. (1997). Mine boundary detection using partially ordered Markov Models, in Statistical and Stochastic Methods in Image Processing II, eds F. Preteux, J. L. Davidson, and E.R. Dougherty. Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 3167. SPIE, Bellingham, WA, 152-163.

Huang, H.C. and Cressie, N. (1997). Multiscale spatial modeling, in 1997 Proceedings of the Section on Statistics and the Environment. American Statistical Association, Alexandria, VA, 49-54.


Cressie, N. (1996). Statistical modeling of environmental data in space and time, in Spatial Accuracy Assessment in Natural Resources and Environmental Sciences: Second International Symposium, eds H.T. Mowrer, R.L. Czaplewski, and R.H. Hamre. General Technical Report RM-GTR-277, USDA Forest Service, Fort Collins, CO, 1-3.

Cressie, N., Olsen, A., and Cook, D. (1996). Massive data sets: Problems and possibilities with application to environmental modeling, in Massive Data Sets: Proceedings of a Workshop. National Academy Press, Washington, DC, 115-119.

Majure, J.J., Cook, D., Cressie, N., Kaiser, M., Lahiri, S., and Symanzik, J. (1996). Spatial CDF estimation and visualization with applications to forest health monitoringComputing Science and Statistics27, 93-101.

Majure, J.J., Cressie, N., Cook, D., and Symanzik, J. (1996). GIS, spatial statistical graphics, and forest health, in Proceedings of Third International Conference/Workshop on Integrating GIS and Environmental Modeling, Santa Fe, NM, January 21-26, 1996. National Center for Geographic Information and Analysis. Santa Barbara, CA. Available on CD and at URL


Hua, X., Davidson, J. L., and Cressie, N. (1995). Mine boundary detection using Markov random field models, in Detection Technologies for Mines and Minelike Targets. Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 2496. SPIE, Bellingham, WA, 626-636.

Stern, H.S. and Cressie, N. (1995). Bayesian and constrained Bayesian inference for extremes in epidemiology, in 1995 Proceedings of the Section on Epidemiology. American Statistical Association, Alexandria, VA, 11-20.


Cook, D., Cressie, N., Majure, J., and Symanzik, J. (1994). Some dynamic graphics for spatial data (with multiple attributes) in a GIS, in Compstat '94. Proceedings of 11th Symposium, Vienna, Austria, eds R. Dutter and W. Grossman. Physica-Verlag, Heidelberg, DE, 105-119.

Davidson, J. L., Talukder, A., and Cressie, N. (1994). Texture analysis using partially ordered Markov models, in Proceedings of International Conference on Image Processing (ICIP-94), Vol. III. IEEE Computer Society Press, Los Alamitos, CA, 402-406.

Symanzik, J., Majure, J., Cook, D., and Cressie, N. (1994). Dynamic graphics in a GIS: A link between ARC/INFO and XgobiComputing Science and Statistics26, 431-435.


Cressie, N. (1993). Spatial prediction in a multivariate setting, in Multivariate Environmental Statistics, eds G. P. Patil and C. R. Rao. North Holland, New York, NY, 99-107.

Davidson, J. L. and Cressie, N. (1993). Markov pyramid models in image analysis, in Image Algebra and Morphological Image Processing IV, eds E. R. Dougherty, P. D. Gader, and J. C. Serra. Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 2030. SPIE, Bellingham, WA, 179-190.

Helterbrand, J. D. and Cressie, N. A. C. (1993). Stochastic recognition of closed object boundaries in images, in Image Algebra and Morphological Image Processing IV, eds E. R. Dougherty, P. D. Gader, and J. C. Serra. Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 2030. SPIE, Bellingham, WA, 240-251.

Majure, J. J. and Cressie N. (1993). Explore: Exploratory spatial data analysis in ARC/INFO, in Proceedings of the Thirteenth Annual ESRI User Conference, Vol. 1. Environmental Systems Research Institute, Redlands, CA, 277-281.


Cressie, N. and Grondona, M. O. (1992). A comparison of variogram estimation with covariogram estimation, in The Art of Statistical Science, ed. K. V. Mardia. Wiley, Chichester, UK, 191-208.


Cressie, N. (1991). Modeling growth with random sets, in Spatial Statistics and Imaging (Proceedings of the 1988 AMS-IMS-SIAM Joint Summer Research Conference), ed. A. Possolo. Institute of Mathematical Statistics, Hayward, CA, 31-45.

Cressie, N. (1991). Small-area prediction of undercount using the general linear modelProceedings of the 1990 Symposium on the Measurement and Improvement of Data Quality. Statistics Canada, Ottawa, 93-105.

Davidson, J. L. and Cressie, N. A. C. (1991). Statistical image algebra: A Bayesian approach, in Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, ed. S. S. Chen. Society of Photo-Optical Instrumentation Engineers (SPIE) Proceedings, Vol. 569. SPIE, Bellingham, WA, 288-297.


Cressie, N. (1990). Weighted smoothing of estimated undercountProceedings of Bureau of the Census 1990 Annual Research Conference. US Bureau of the Census, Washington, DC, 301-325.


Cressie, N. (1988). Estimating census undercount at national and subnational levels with discussionProceedings of Bureau of the Census Fourth Annual Research Conference. US Bureau of the Census, Washington, DC, 123-150.


Cressie, N. (1987). Estimating undercount in the U. S. Decennial CensusBulletin of the International Statistical Institute52, Contributed Papers Volume, 85-86.

Cressie, N. (1987). Spatial data analysis and modeling of regional variables, in 1987 Sino-American Statistical Meeting, Beijing, Contributed Papers Volume, 108-111.

Cressie, N. (1987). Spatial prediction and site selectionProceedings of ASA/ EPA Conferences on Interpretation of Environmental Data. III Sampling and Site Selection in Environmental Studies. Environmental Protection Agency, Washington, DC, 25-30.

Cressie, N. A. C. and Guo, R. (1987). Mapping variables, in Proceedings of the NCGA Conference, Computer Graphics '87, Vol. III. National Computer Graphics Association, McLean, VA, 521-530.


Cressie, N. (1985). A geostatistical analysis of the Mercer and Hall wheat dataBulletin of the International Statistical Institute51, Contributed Papers Volume, 277-278.

Cressie, N. (1985). The underlying structure of empirical Bayes methodsRassegna di Metodi Statistici ed Applicazioni5, 19-31.

Cressie, N. (1985).  Kriging nonstationary data, in Proceedings of the 1985 Meeting of the Italian Statistical Society on Statistics and Natural Resources, 35-66.


Cressie, N. (1984). Modelling sets, in Multifunctions and Integrands, ed. G. Salinetti. Springer Lecture Notes in Mathematics, No. 1091, Springer, New York, NY, 138-149.


Cressie, N. (1982). Empirical Bayes estimation in quality controlRassegna di Metodi Statistici ed Applicazioni2, 57-77.


Cressie, N. (1981). How useful are asymptotic results in extrema problems? Bulletin of the International Statistical Institute49, Contributed Papers Volume, 53-56.

Keightley, D. D. and Cressie, N. A. C. (1981). Analysis of hormone receptor assay data by Scatchard, Reciprocal, and Woolf plots (with discussion), in Estrogen Receptor Assays in Breast Cancer, eds G. A. Sarfarty et al. Masson, New York, 210-224.


Cressie, N. (1979). Straight line fitting and variogram estimation (with discussion)Bulletin of the International Statistical Institute48, Book 3, 573-580.


Cressie, N. (1977). Clustering on the circleBulletin of the International Statistical Institute47, Book 4, 124-127.


Other Publications (including Book Reviews, Comments, Interviews, etc.)


Article: Space, uncertainty, and the environment: honouring the distinguished career of Noel Cressie by Alfred Stein and Christopher K. Wikle, in Spatial Statistics, 61, 100835 (2024) (doi:10.1016/j.spasta.2024.100835).


Bibliographic entry on Noel A.C. Cressie, by Jay M. Ver Hoef, in Encyclopedia of Mathematical Geosciences, eds B. S. Daya Sagar, Q. Cheng, J. McKinley, and F. Agterberg. Springer, Cham, CH, pp. 214-215 (2023) (doi:10.1007/978-3-030-26050-7_388-2).

Bibliographic entry on Geoffrey. S. Watson, by N. Cressie and C. A. Gotway Crawford, in Encyclopedia of Mathematical Geosciences, eds B. S. Daya Sagar, Q. Cheng, J. McKinley, and F. Agterberg. Springer, Cham, CH, pp.1625-1626 (2023) (doi:10.1007/978-3-030-26050-7_369-1).

Robodebt not only broke the laws of the land it also broke laws of mathematics, by N. Cressie, in The Conversation  (17 March 2023) (

Submission to the Royal Commission Enquiry into the Robodebt Scheme, by N. Fisher, D. Trewin, and N. Cressie, published online and listed in the Royal Commission Report, 07 July 2023 (

World's best statistical practice saves lives, by D. Trewin, N. Fisher, and N. Cressie. Submission to Australian Government COVID-19 Response Inquiry, Prime Minister and Cabinet (3 pp.), 05 December 2023. 


Comment: Nonparametric empirical Bayes prediction, by N. Cressie, a comment on JASA Theory and Methods 2022 Invited Paper “Nonparametric empirical Bayes analysis” by Nikolaos Ignatiadis and Stefan Wager. Journal of the American Statistical Association117, 1167-1170 (2022) (doi:10.1080/01621459.2022.209604)


Computing for net zero: how digital technology can create a ‘control loop for the protection of the planet’, by Andy Hopper and 16 co-contributors, including N. Cressie. Briefing 2 of Climate Change: Science and Solutions. Royal Society: London, UK (12pp.) (2021).


Comment: When is it data science and when is it data engineering? by N. Cressie, a comment on “Prediction, estimation, and attribution” by Bradley Efron. Journal of the American Statistical Association115, 660-662 (2020).


Comment by N. Cressie, on “Visualizing spatiotemporal models with virtual reality: from fully immersive environments to applications in stereoscopic view” by S. Castruccio, M.G. Genton, and Y. Sun. Journal of the Royal Statistical Society, Series A182, 429 (2019).

Interview of N. Cressie: “A conversation with Noel Cressie” by Christopher K. Wikle and Jay M. Ver Hoef. Statistical Science34, 349-359 (2019).


Interview of N. Cressie: ABC Illawarra, 25 May 2018, “Election to Fellowship of the Australian Academy of Science” (2018) (


A Common Task Framework (CTF) for objective comparison of spatial prediction methodologies, by C. K. Wikle, N. Cressie, A. Zammit-Mangion, and C. Shumack. Stats & Data Science Views, Wiley, Chichester, UK (2017)

Summary of “Workshop on Spatial and Spatio-Temporal Design and Analysis for Official Statistics,” by S. H. Holan, N. Cressie, C. K. Wikle, J. R. Bradley, and M. Simpson. NSF-Census Research Network report, archived at Cornell University Library (5 pp.) (2017). 

A new map of global Ecological Marine Units: An environmental stratification approach, by R. Sayre (and 31 co-authors, including N. Cressie), a Special Publication of the American Association of Geographers, Washington, DC, USA (35 pp.) (2017).

Uncertainty, Statistical Science, and Black Swans, by N. Cressie. Stats & Data Science Views, Wiley, Chichester, UK (2017) (


Poster: Bivariate modelling of poverty and unemployment in Missouri, by R. McDonald, A. Zammit-Mangion, and N. Cressie, presented at the Workshop on Spatial and Spatio-Temporal Design and Analysis for Official Statistics, May 2016, Columbia, MO, USA (2016).

Interview of N. CressieABC Illawarra, Friday, 17 June, 2016 “OCO-2 Update
( (2016).

Poster: Quantifying weights for fitting an errors-in-variables model to TCCON and OCO-2 calibration data, by B. Zhang, N. Cressie, and D. Wunch, presented at OCO-2 Science Team Meeting, October 2016, Boulder, CO, USA (2016).


Comment: Capturing multivariate spatial dependence: Model, estimate, and then predict, by N. Cressie, S. Burden, W. Davis, P. Krivitsky, P. Mokhtarian, T. Seusse, and A. Zammit-Mangion, a comment on “Cross-covariance functions for multivariate geostatistics” by M. G. Genton and W. Kleiber. Statistical Science30, 170-175 (2015).

Comment: Spatial sampling designs depend as much on “how much?” and “why?” as on “where?”, by N. Cressie and R.L. Chambers, a comment on “Optimal design in geostatistics under preferential sampling” by G. da Silva Ferreira and D. Gamerman. Bayesian Analysis10, 741-748 (2015).

Poster: 95% prediction regions: Multivariate uncertainty quantification for retrieved atmospheric states, by N. Cressie and S. Burden, presented at the Eleventh International Workshop on Greenhouse Gas Measurements from Space, June 2015, Pasadena, CA, USA (IWGGMS-11) (2015)

Interview of N. Cressie: “Measuring and mapping sources and sinks of carbon dioxide in the atmosphere,” in ArcWatch, August 2015


Interview of A. Braverman and N. Cressie: “The search for CO2: NASA to launch satellite to map sources and sinks,” in Biometric Bulletin, Vol. 31, Issue 1, January-March 2014.

Interview of N. Cressie: ABC Radio National’s Drive program with Waleed Aly, Thursday, 3 July 2014, “NASA satellite to search for climate change clues

Interview of N. Cressie: ABC Illawarra with Nick Rheinberger, Friday, 4 July 2014, “UOW and NASA unite for carbon dioxide counting mission

Interview of N. Cressie: Australian Broadcasting Corporation’s “StarStuff,” Wednesday, 9 July 2014, “NASA launches satellite to monitor Earth’s CO2

Working Paper: Visualizing massive spatial datasets using multi-resolution global grids, by T. Stough, A. Braverman, N. Cressie, E. Kang, A. Michalak, H. Nguyen, and K. Sahr. NIASRA Working Paper 05-14 (24 pp.) (2014).

White Paper: Statistical science: Contributions to the administration’s research priority on climate change, by B. Sanso et al. (11 co-authors, including N. Cressie), written by the American Statistical Association’s Advisory Committee for Climate Change Policy, April 2014 (5 pp.).


Interview of N. Cressie: "Award-winning Wiley author takes on statistical role at NASA,” in Stats & Data Science Views, John Wiley and Sons (2013)

Interview: “Spatio-Temporal Statistics as its own discipline: Noel Cressie and Christopher Wikle on their award-winning collaboration,” in Stats & Data Science Views, John Wiley and Sons (2013)

Blog: Hierarchical spatio-temporal models and survey research, by C.K. Wikle, S.H. Holan, and N. Cressie, in Stats & Data Science Views, John Wiley and Sons (2013)

Column: How can survey estimates of small areas be improved by leveraging social-media data?, by N. Cressie, S.H. Holan, and C.K.Wikle. Ask the Expert Column, in The Survey Statistician, Newsletter of the International Association of Survey Statisticians, No. 68, July 2013, pp. 14-15 (2013).

Interview of N. Cressie:, the official blog of Methods in Ecology and Evolution, published by the British Ecological Society (2013)

Technical Brief: Spatial statistical data fusion (SSDF), on work by A. Braverman, N. Cressie, and H. Nguyen. NASA Tech Briefs37, November 2013

Foreword: Spatio-Temporal Design: Advances in Efficient Data Acquisition, eds J. Mateu and W. Müller. Wiley, Chichester, UK, pp. xix-xx (2013).


Perspectives in statistics for young statisticians, by N. CressieStatistical Society of Australia, Inc. (SSAI) Newsletter, September 2012, 22-23 (2012).

Thoughts on Bayesian statistical inference for regional climate projections in North America, by N. CressieSAMSI Blog (2012)


Comment, by N. Cressie, a comment on “Spatial prediction in the presence of positional error” by T.R. Fanshawe and P.J. Diggle. Environmetrics22, 125-126 (2011).

Editorial: Special issue on time series in the environmental sciences, by N. Cressie and S.H. Holan. Journal of Time Series Analysis32, 337-338 (2011).

Tutorial on Fixed Rank Kriging (FRK) of CO2 data, by M. Katzfuss and N. Cressie. Department of Statistics Technical Report No. 858, The Ohio State University, Columbus, OH (23 pp.) (2011).

Tribute to Julian Besag, 1945-2010: A tribute by N. Cressie (2011)


Comment: Statistical dependence in stream networks, by N. Cressie and D. O’Donnell, a comment on “A moving average approach for spatial statistical models for stream networks” by J. Ver Hoef and E. Peterson. Journal of the American Statistical Association105, 18-21 (2010).

Comment: Hierarchical statistical modeling for paleoclimate reconstruction, by N. Cressie and M. P. Tingley, a comment on “The value of multi-proxy reconstruction of past climate” by B. Li, D. Nychka, and C. Ammann. Journal of the American Statistical Association105, 895-900 (2010).

White Paper: Spatial and temporal interpolation of environmental data, by T. Smith, P. Jones, E. Kent, M. Cox, N. Cressie, D. Dee, and R. Smith, written for the Workshop on Creating Surface Temperature Datasets to Meet 21st Century Challenges, Met Office Hadley Centre, Exeter, UK, September 2010 (8 pp.) (2010).

White Paper: The (statistical) science of sustainability, by N. Cressie, written for the Workshop on Mathematical Challenges for Sustainability, DIMACS Center, Rutgers University, NJ, November 2010 (4 pp.) (2010).


Where, When, and then Why, 2009 Fisher Lecture given by Noel Cressie, at the Joint Statistical Meetings, Washington DC, August 2009

Statistical Counterpoint, by N. Cressie, O. Ahlqvist, H. Ban, and the Synchronous Objects team, one of the Synchronous Objects for “One Flat Thing, reproduced,” a webpage showing visualization/animation of dance (2009)

Noel Cressie on Dance and Statistics,” a blog on Synchronous Objects for “One Flat Thing, reproduced” (2009)


Comment on “Modern statistics for spatial point processes” by J. Moller and R. Waagepetersen. Scandinavian Journal of Statistics34, 690-691 (2007).


Comment on “Markov chain Monte Carlo methods for high dimensional inversion in remote sensing” by H. Haario et al. Journal of the Royal Statistical Society B66, 638 (2004).


El Niño forecasting using Hierarchical Dynamic (HiDyn) Models: A web-based product. The International Environmetrics Society (TIES) Newsletter, Vol. 9, November 2003, pp. 15, 16 (2003).

Modifying the FDR procedure for use with FMRI data, by M. Pavlicova, N. Cressie, T. J. Santner, and A. Algaze. NeuroImage19, S919 (2003), where notice of the poster presentation appears under the title, “Using enhanced FDR to find activation in FMRI images.” (2003)


Environmental Data Seminar at The Ohio State UniversityThe International Environmetrics Society (TIES) Newsletter, Vol. 8, May 2002, pp. 10, 11.

The perspective of quantitative science in the debate about environmental degradation: Panel discussion. TIES Newsletter, Vol. 8, November 2002, pp. 10, 11.

Directed Markov point processes – characterisation and construction, by A. J. Baddeley, M. G. Nair, and N. CressieDepartment of Statistics Technical Report No. 693, The Ohio State University, Columbus, OH (29 pp.) (2002).


Environmental and spatial statistical research at The Ohio State UniversityNewsletter of the American Statistical Association Section on Statistics and the Environment, Vol. 4, Summer 2000, pp. 5, 7.

Spatial statistics in the Life and Medical SciencesBiostatistics Newsletter, The Ohio State University (2000).

Workshop on Hierarchical Modeling in Environmental StatisticsThe International Environmetrics Society (TIES) Newsletter, Vol. 6, August 2000, p. 9.

Workshop on Hierarchical Modeling in Environmental Statistics (joint with T. Gregoire). Amstat News, July 2000, p. 51.


Letter to the EditorAmerican Journal of Human Biology11, 433-434 (1999).

Environmental statistics at The Ohio State UniversityNewsletter of the American Statistical Association Section on Statistics and the Environment, Vol. 3, Summer 1999, p. 3.

ENVR committee structureAmstat News, November 1999, p. 46.


Letter to the Editor. American Journal of Human Biology, 10, 1-2 (1998).

Comment on “Model-based geostatistics” by P.J. Diggle, J.A. Tawn, and R.A. Moyeed. Applied Statistics47, p. 335 (1998).

Obituary (joint with C. G. Crawford): Geoffrey S. Watson, 1921-1998International Association for Mathematical Geology Newsletter, No. 56, June 1998, p. 9.

Book review (joint with J. Symanzik) of “Variowin - Software for Spatial Data Analysis in 2D” by Y. Pannatier. Computational Statistics13, 419-422 (1998).

Environmental statistics and ENVR. Newsletter of American Statistical Association Section on Statistics and the Environment, Vol. 2, (1998).

ENVR 1998 award recipients and newsletterAmstat News, August/September 1998, p. 29.

ENVR - The year in reviewAmstat News, December 1998, p. 42.

Comment (joint with C.K. Wikle) on: Strategies for dynamic space-time statistical modeling: discussion of “The kriged Kalman filter” by K.V. Mardia, C. Goodall, E. Redfern, and F.J. Alonso. Test, 7, 257-264 (1998).

Abstract (joint with J. Gabrosek and H. Huang): Spatial data analysis, statistical modeling and spatial prediction of earth’s total column ozoneComputing Science and Statistics30, p. 42 (1998).


Book review of “Introduction to Disjunctive Kriging and Nonlinear Geostatistics” by J. Rivoirard. SIAM Review39, 337-340 (1997).

Cook, D., et al. (6 co-authors, including Cressie, N.). Exploring associations among mid-Atlantic stream indicators using dynamic multivariate graphics and geographic mapping in a highly immersive virtual reality environmentComputing Science and Statistics29, 220 (1997).

Comment on “Trends in ozone exposure and population density in Harris County, Texas” by R. J. Carroll, R. Chen, T. H. Li, H. J. Newton, H.Schmiediche, N. Wang, and E. I. George. Journal of the American Statistical Association92, 411-413 (1997).

Comment on “Random sampling or geostatistical modelling? Choosing between design-based and model-based sampling strategies for soil” by D.J. Brus and J.J. de Gruijter. Geoderma80, 51-52 (1997).

Comment (joint with H.C. Huang) on “On Bayesian analysis of mixtures with an unknown number of components” by S. Richardson and P.J. Green. Journal of the Royal Statistical Society B59, 777 (1997).

Reply (joint with S.S. Carroll) to Discussion by David C. Garen, of “A comparison of geostatistical methodology used to estimate snow water equivalent” by S.S. Carroll and N. Cressie, Journal of the American Water Resources Association33, 221-222 (1997).

Environmental statistics at Iowa State UniversityNewsletter of American Statistical Association Section on Statistics and the Environment, Vol. 1, (1997).

American Statistical Association Section on Statistics and the Environment: Strategic plan reviewAmstat News, November 1997, 27-28.


Book review of “Optimally Sequentially Planned Decision Procedures” by N. Schmitz. Metrika42, 141-143 (1995).


Comment (joint with M. S. Kaiser) on “Small area estimation: An appraisal” by M. Ghosh and J. N. K. Rao. Statistical Science, 9, 76-80 (1994).

Comment on “An approach to statistical spatial-temporal modeling of meteorological fields” by M. S. Handcock and J.R. Wallis. Journal of the American Statistical Association89, 379-382 (1994).

Editorial: Limits of detectionChemometrics and Intelligent Laboratory Systems22, 161-163 (1994).


Report to Environmental Protection Agency (joint with L. Young, W. S. Liggett, R. J. Little, and J. H. Matis); “Review of EMAP Statistics and Design, Review Meeting Held November 4-6, 1991, San Francisco, California” (20 pp.) (1992).

Comment on “Should we have adjusted the Census of 1980?” by D. A. Freedman and W. C. Navidi. Survey Methodology, 18, 32-34 (1992).


Book review of “Robust Estimation and Testing” by R. G. Staudte and S. J. Sheather. Mathematical Reviews91, 3307-3308 (1991).

Response (joint with D. Ruppert and R. Carroll) to “Generalized Linear Models for Enzyme Kinetic Data” by J. A. Nelder. Biometrics47, 1610-1615 (1991).

Produced and participated in one-hour videotape, “Oscar Kempthorne: From Observation to Inference,” for American Statistical Association Committee for the Filming of Distinguished Statisticians (1991)

First International Conference/Workshop on Integrating Geographic Information Systems and Environmental ModelingAmstat News, December 1991, 21 (1991).

Hierarchical testing of parametric models using the power-divergence family of test statistics, by F. M. Medak and N. CressieStatistical Laboratory Preprint, No. 91-14, Iowa State University, Ames, IA (1991).


Book review of “Transformation and Weighting in Regression” by R. J. Carroll and D. Ruppert. Mathematical Reviews90, 695-696 (1990).

Reply to G. Wahba’s Letter to the EditorAmerican Statistician44, 256-258 (1990).

Report to Special Advisory Panel, U. S. Bureau of the Census, on Final Guidelines for Adjustment of the 1990 Decennial Census (14 pp.) (1990).


Comment (joint with F. Pesarin) on “Space-time modelling with long-memory dependence: Assessing Ireland’s wind resource” by J. Haslett and A. E. Raftery. Applied Statistics38, 31-32 (1989).

Book review of “Asymptotics for Generalized Chi-Square Goodness-of-Fit Tests” by F. C. Drost. Journal of the Royal Statistical Society A152, 258-259 (1989).

Letter to the EditorGeostatistics: An Interdisciplinary Geostatistics Newsletter3, Spring 1989, 15.


To adjust or not to adjust: U. S. census countsStat Lab News, No. 2, October 1988, 7-8.

Editorial: Statistics in chemistryChemometrics and Intelligent Laboratory Systems3, 249-250 (1988).


Book review of “Spatial Data Analysis by Example” by G. Upton and B. Fingleton. Technometrics29, 114-116 (1987).

Comment on “Census undercount adjustment and the quality of geographic population distributions” by A. L. Schirm and S. H. Preston. Journal of the American Statistical Association82, 980-983 (1987).

Written testimony given to Congressional Hearing called by U. S. House of Representatives Committee on Post Office and Civil Service, Subcommittee on Census and Population, on “The Impact of Population Undercount,” San Francisco, CA, 8/17/87.

Statistics for spatial dataStat Lab News, No. 1, June 1987, pp. 2, 6, 7.

Exact interpolationGeostatistics: An Interdisciplinary Geostatistics Newsletter1, Summer 1987, 11-13.

Comment on “Recursive methods in image processing” by P. J. Green and D. M. Titterington. Bulletin of the International Statistical Institute, 52, Book 4, 100-101 (1987).

Comment on “Application of some empirical Bayes methods to small area estimation” by E. Spjotvoll and I. Thomsen. Bulletin of the International Statistical Institute52, Book 4, 473 (1987).

Mixing ergodicity and geostatisticsGeostatistics: An Interdisciplinary Geostatistics Newsletter2, Autumn 1987, 9-12.


Comment on “Size and shape spaces for landmark data in two dimensions” by F. L. Bookstein. Statistical Science1, 226 (1986).

Comment on “Statistical synthetic estimates of undercount for small areas” by C. T. Isaki, G. J. Diffendal, and L. K. Schultz. Proceedings of Bureau of the Census Second Annual Research Conference. U. S. Bureau of the Census, Washington, DC, 580-583 (1986).

ASA/NSF/Census Fellowship Program: Some perceptions and suggestions. An evaluation of the ASA/NSF/Census Fellowship Program, 1980-1986 (a report to the American Statistical Association under the chairmanship of W. Allen Spivey), A51-A58 (1986).


Comment on “Some aspects of the spline smoothing approach to nonparametric regression curve fitting” by B.W. Silverman. Journal of the Royal Statistical Society B47, 34-35 (1985).

Response to a Letter to the Editors (joint with L. J. Sheffield and H. J. Whitford). Journal of Chronic Diseases38, 1030 (1985).

Intensity estimation in a spatial model of overlapping particles, with G. M. Laslett and S. Liow. Unpublished manuscript (12 pp.) (1985).


Book review of “Statistics on Spheres” by G. S. Watson. Journal of the American Statistical Association79, 733 (1984).


Revised the book, “Image Analysis and Mathematical Morphology” by J. Serra. Academic Press, London, UK (1982).

Statistics in Resource Development theme of the 6th Australian Statistical Conference (Melbourne, 23-27 August 1982). Bulletin of Australian News in Geomathematics, February, 1982.

Letter to the EditorThe Statistician31, 117 (1982).

Book review of “Applied Regression Analysis, Second Edition” by N. R. Draper and H. Smith. Australian Journal of Statistics24, 387-390 (1982).

Short course on geostatisticsStatistical Society of Australia Newsletter, No. 21, November 1982.


Comment on “Random fields in models in surface science” by R. J. Adler. Bulletin of the International Statistical Institute49, Book 2, 680-681 (1981).

Comment on “The relation of sums and extremes of random variables” by T. Mori. Bulletin of the International Statistical Institute, 49, Book 2, 899-900 (1981).


Random set limit theorems (Abstract in Proceedings of the 8th Conference on Stochastic Processes). Advances in Applied Probability, 11, 281-282 (1979).


Book review of “Lecture Notes on Queuing Systems” by G. Conolly. Journal of the Royal Statistical Society A140, 97-98 (1977)..

Comment on “Estimation of spatial distributions from point sources with applications to air pollution measurement” by P. Switzer. Bulletin of the International Statistical Institute47, Book 2, 144 (1977).


Testing for uniformity against a clustering alternative. Unpublished Ph.D. Thesis, Princeton University (153 pp.) (1975).


A two-dimensional random walk (Abstract in Proceedings of the 3rd Conference on Stochastic Processes). Advances in Applied Probability6, 248-249 (1974).