000			nam a22 4500
999			_c32684 _d32684
008			240214b xxu||||| |||| 00| 0 eng d
020			_a9780367146399
082			_a519.535 _bVAN
100			_aVan Lieshout, M. N. M.
245			_aTheory of spatial statistics : a concise introduction
260			_aBoca Raton : _bCRC Press, _c2019
300			_axi, 148 p. ; _bill., _c26 cm.
365			_b56.99 _c₤ _d110.20
490			_vTexts in statistical science
504			_aIncludes bibliographical references and index.
520			_aA 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.
650			_aMathematics Applied
650			_aProbability
650			_aStatistics General
650			_aSpatial analysis
650			_aRandom field modelling
650			_aBounded Borel set
650			_aCovariance function
650			_aEstimator
650			_aPoisson process
650			_aProbability density
650			_aSemi-variogram
942			_2ddc _cBK