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Decomposition of Variance for Spatial Cox Processes
Author(s) -
JALILIAN ABDOLLAH,
GUAN YONGTAO,
WAAGEPETERSEN RASMUS
Publication year - 2013
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/j.1467-9469.2012.00795.x
Subject(s) - mathematics , cox process , point process , covariance , statistics , spatial analysis , variance (accounting) , decomposition , covariance function , variance function , spatial dependence , econometrics , regression analysis , ecology , poisson process , poisson distribution , accounting , business , biology
. Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.