9780521424202 - statistical inference for spatial processes von ripley, b. d. (5 Ergebnisse)
- Softcover
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- Softcover
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Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,350grams, ISBN:9780521424202.
- Softcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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- Softcover
Anbieter: Kennys Bookstore, Olney, MD, USAKennys Bookstore
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Zustand: New. This book introduces statistical inference in spatial statistics and its applications. Num Pages: 160 pages, 50 b/w illus. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 228 x 152 x 9. Weight in Grams: 240. . 1991. Illustrated. paperback. . . . . Books ship from the US and Ireland.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The study of spatial processes and their applications is an important topic in statistics and finds wide application particularly in computer vision and image processing. This book is devoted to statistical inference in spatial statistics and is inte…nded for specialists needing an introduction to the subject and to its applications.One of the themes of the book 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, the author 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. Thus, the book will find wide appeal to researchers in computer vision, image processing, and those applying microscopy in biology, geology and materials science, as well as to statisticians interested in the foundations of their discipline.
