Theory of Spatial Statistics

<p><strong>Theory of Spatial Statistics: A Concise Introduction</strong> 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.<br><br>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.<br><br><strong>Features</strong>* Presents the mathematical foundations of spatial statistics.<br>* Contains worked examples from mining disease mapping forestry soil and environmental science and criminology.<br>* Gives pointers to the literature to facilitate further study.<br>* Provides example code in R to encourage the student to experiment.<br>* Offers exercises and their solutions to test and deepen understanding.<br><br>The book is suitable for postgraduate and advanced undergraduate students in mathematics and statistics.</p>