Noel Cressie

Noel Cressie (born 1950 in Fremantle, Australia) is an Australian and American statistician.^[1][2] He is a Distinguished Professor and Director, Centre for Environmental Informatics, at the University of Wollongong in Wollongong, Australia.

Cressie is best known for having brought disparate statistical methodologies into a nascent discipline known as Spatial Statistics. In his widely cited book, Statistics for Spatial Data,^[3] Cressie established a general spatial model that unified statistics for geostatistical data, regular and irregular lattice data, point patterns, and random sets. Since the 1980s, he has been a developer of statistical theory, methodology and applications for spatial and spatio-temporal data. Since the 2000s, this methodology has emphasized hierarchical statistical modeling, which was integrated into his most recent book Statistics for Spatio-Temporal Data.^[4] It has been applied in areas of ‘big science,’ such as remote sensing of Earth on a global scale,^[5] understanding the global carbon cycle and its effect on climate change,^[6] Greenland ice-sheet dynamics,^[7] and disease mapping.^[8]

Cressie was trained in Australia and the USA and obtained his Ph.D. in Statistics from Princeton University, USA, advised by Geoffrey Watson and taught by both Watson and John Tukey. He has spent the majority of his professional life in the USA as professor and distinguished professor at both Iowa State University and The Ohio State University. Since 2012, he has been professor and distinguished professor at the University of Wollongong, Australia.

Over the course of his statistical career, Cressie has written or coauthored three books and more than 250 articles in scholarly journals.^[9] His accomplishments have made him the recipient of a number of awards, including Fellow of the American Statistical Association (ASA),^[10] Fellow of the Institute of Mathematical Statistics,^[11] Fellow of the Spatial Econometrics Association,^[12] and Elected Member of the International Statistical Institute.^[13] In 2009, he received one of the highest awards in statistical science, the R.A. Fisher Lectureship, from the Committee of Presidents of Statistical Societies (COPSS). His book, “Statistics for Spatio-Temporal Data” (2011), by Noel Cressie and Christopher K. Wikle, received two awards: the 2011 PROSE Award in the Mathematics category (for PROfessional and Scholarly Excellence, given by the Association of American Publishers); and the 2013 DeGroot Book Prize (awarded every two years by the International Society for Bayesian Analysis). More recently, Cressie was awarded the Pitman Medal^[14] in 2014 by the Statistical Society of Australia in recognition of his outstanding achievement in, and contribution to, the discipline of Statistics. In 2016, he received the Barnett Award by the Royal Statistical Society for excellence in environmental statistics.^[15]

His later work is in environmental informatics, emphasizing uncertainty quantification and using tools from the fields of Statistics, Mathematics, Computing, and Visualization. His main area of application has been in remote sensing of the environment, and this initiative has continued into the second stage of his professional career in Australia.

Selected Publications

• Goodness-of-Fit Statistics for Discrete Multivariate Data, by Timothy R. C. Read and Noel A. C. Cressie. Springer, New York, NY, 1988 (211 pp.)
• Statistics for Spatial Data, by Noel A. C. Cressie. Wiley, New York, NY, 1991 (900 pp.). Revised edition: Wiley, New York, NY, 1993 (900 pp.). Paperback edition in the Wiley Classics Library: Wiley, Hoboken, NJ, 2015 (900 pp.)
• Statistics for Spatio-Temporal Data, by Noel Cressie and Christopher K. Wikle. Wiley, Hoboken, NJ, 2011 (588 pp.)
• Cressie, N. (1990). The origins of kriging. Mathematical Geology, 22, 239-252.
• Cressie, N. (1989). Empirical Bayes estimation of undercount in the Decennial Census. Journal of the American Statistical Association 84, 1033-1044.
• Cressie, N. and Hulting, F. L. (1992). A spatial statistical analysis of tumor growth. Journal of the American Statistical Association 87, 272-283.
• Cressie, N. and Huang, H.C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association 94, 1330-1340. (Correction: 2001, Vol. 96, p. 784.)
• Wikle, C.K. and Cressie, N. (1999). A dimension-reduced approach to space-time Kalman filtering. Biometrika 86, 815-829.
• Cressie, N. and Johannesson, G. (2008). Fixed rank kriging for very large spatial data sets. Journal of the Royal Statistical Society, Series B 70, 209-226.
• Cressie, N., Shi, T., and Kang, E.L. (2010). Fixed rank filtering for spatio-temporal data. Journal of Computational and Graphical Statistics 19, 724-745.
• Nguyen, H., Katzfuss, M., Cressie, N., and Braverman, A. (2014). Spatio-temporal data fusion for very large remote sensing datasets. Technometrics 56, 174-185.
• Cressie, N. and Kang, E.L. (2016). Hot enough for you? A spatial exploratory and inferential analysis of North American climate-change projections. Mathematical Geosciences 48, 107-121.

External links

• Google Scholar Profile
• Curriculum vitae

References