Theory of Spatial Statistics (A Concise Introduction)
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Product Details
Author:
M.N.M. van Lieshout
Format:
Paperback
Pages:
182
Publisher:
CRC Press (March 11, 2019)
Language:
English
ISBN-13:
9780367146399
Weight:
18.25oz
Dimensions:
6.125" x 9.1875"
File:
TAYLORFRANCIS-TayFran_260406043133783-20260406.xml
Folder:
TAYLORFRANCIS
List Price:
$89.99
Series:
Chapman & Hall/CRC Texts in Statistical Science
Case Pack:
40
As low as:
$85.49
Publisher Identifier:
P-CRC
Discount Code:
H
Country of Origin:
United States
Pub Discount:
30
Imprint:
Chapman and Hall/CRC
Overview
Theory of Spatial Statistics: A Concise Introduction presents the most important models used in spatial statistics, including random fields and point processes, from a rigorous mathematical point of view and shows how to carry out statistical inference. It contains full proofs, real-life examples and theoretical exercises. Solutions to the latter are available in an appendix.
Assuming maturity in probability and statistics, these concise lecture notes are self-contained and cover enough material for a semester course. They may also serve as a reference book for researchers.
Features
* Presents the mathematical foundations of spatial statistics.
* Contains worked examples from mining, disease mapping, forestry, soil and environmental science, and criminology.
* Gives pointers to the literature to facilitate further study.
* Provides example code in R to encourage the student to experiment.
* Offers exercises and their solutions to test and deepen understanding.
The book is suitable for postgraduate and advanced undergraduate students in mathematics and statistics.
Assuming maturity in probability and statistics, these concise lecture notes are self-contained and cover enough material for a semester course. They may also serve as a reference book for researchers.
Features
* Presents the mathematical foundations of spatial statistics.
* Contains worked examples from mining, disease mapping, forestry, soil and environmental science, and criminology.
* Gives pointers to the literature to facilitate further study.
* Provides example code in R to encourage the student to experiment.
* Offers exercises and their solutions to test and deepen understanding.
The book is suitable for postgraduate and advanced undergraduate students in mathematics and statistics.
