Statistical Inference for Spatial Processes


Statistical Inference for Spatial Processes

This book is designed for specialists needing an introduction to statistical inference in spatial statistics and its applications. One of the author's themes is to show how these techniques give new insights into classical procedures (including new examples in likelihood theory) and newer statistical paradigms such as Monte-Carlo inference and pseudo-likelihood. Professor Ripley also stresses the importance of edge effects and of the lack of a unique asymptotic setting in spatial problems. Throughout, he discusses the foundational issues posed and the difficulties, both computational and philosophical, which arise. The final chapters consider image restoration and segmentation methods and the averaging and summarizing of images.


 Reviews:

"...required reading for anyone interested in the theory of spatial processes." Biometrics

"...provides an excellent snapshot of the spatial statistics in 1987 and ideas for more recent research topics. Although the mathematical content is quite sophisticated, the results are well explained....I highly recommend it to users of spatial statistics, particularly users of spatial point processes and spatial image models." James R. Koehler, Technometrics

No references available.