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Testing Local Independence between Two Point Processes
Author(s) -
Allard Denis,
Brix Anders,
Chadoeuf Joël
Publication year - 2001
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2001.00508.x
Subject(s) - point process , independence (probability theory) , contrast (vision) , range (aeronautics) , statistics , point (geometry) , set (abstract data type) , econometrics , computer science , mathematics , statistical hypothesis testing , spatial dependence , data mining , algorithm , artificial intelligence , geometry , materials science , composite material , programming language
Summary. Dependencies between two types of points in a spatial point process can be due either to a real dependence between the two types or to the dependence on common underlying variables. We propose a global test for dependence between two point processes that is valid for a wide range of models. In contrast with previously proposed methods, it is based on a number of local test statistics, which makes it possible to map the local association between the two processes. The behavior of the test is evaluated by a simulation study. It is then applied to a vegetation pattern data set from Burkina Faso.