Statistical Inference for Spatial Processes (Paperback)

B.D. Ripley

ISBN 10: 0521424208 / ISBN 13: 9780521424202

Edité par Cambridge University Press, Cambridge, 1991

A propos de cet article

Paperback. 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. This book introduces statistical inference in spatial statistics and its applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780521424202

Détails bibliographiques

Titre : Statistical Inference for Spatial Processes ...

Éditeur : Cambridge University Press, Cambridge

Date d'édition : 1991

Reliure : Paperback

Etat : new

A propos de ce titre

Synopsis :

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 intended for specialists needing an introduction to the subject and to its applications. One of the themes of the book is the demonstration of 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 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 summarising 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.