Looking for an examination copy?
This title is not currently available for examination. However, if you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact firstname.lastname@example.org providing details of the course you are teaching.
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.Read more
- New paperback
- Subject matter has wide applications - of particular note is that to computer vision and image processing
Reviews & endorsements
"...required reading for anyone interested in the theory of spatial processes." BiometricsSee more reviews
"...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
Not yet reviewed
Be the first to review
Review was not posted due to profanity×
- Date Published: July 1991
- format: Paperback
- isbn: 9780521424202
- length: 160 pages
- dimensions: 229 x 152 x 9 mm
- weight: 0.24kg
- contains: 50 b/w illus.
- availability: Available
Table of Contents
1. Likelihood analysis for spatial Gaussian processes
2. Edge correction for spatial point processes
3. Parameter estimation for Gibbsian point processes
4. Modelling spatial images
5. Summarizing binary images.
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email email@example.comRegister Sign in
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.Continue ×
Are you sure you want to delete your account?
This cannot be undone.
Thank you for your feedback which will help us improve our service.
If you requested a response, we will make sure to get back to you shortly.×