Inference for Clustered Inhomogeneous Spatial Point Processes

We propose a method to test for significant differences in the levels of clustering between two spatial point processes (cases and controls) while taking into account differences in their first-order intensities. The key advance on earlier methods is that the controls are not assumed to be a Poisson...

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Vydáno v:	Biometrics Ročník 65; číslo 2; s. 423 - 430
Hlavní autoři:	Henrys, P. A., Brown, P. E.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Malden, USA Blackwell Publishing Inc 01.06.2009 Wiley-Blackwell Publishing Blackwell Publishing Ltd
Témata:	adults Algorithms Altitude Biometric Methodology Biometrics biometry Biometry - methods Biostatistics Cluster Analysis Clustering Computer Simulation Data Interpretation, Statistical diagnostic techniques Ecology Environmental epidemiology Epidemiologic Research Design Inference Inhomogeneous methods Null hypothesis P values Pattern Recognition, Automated Point estimators Poisson process Proportional Hazards Models Reproducibility of Results Risk Assessment Risk Assessment - methods Sampling distributions Sensitivity and Specificity Spatial point processes Spatial points Statistical methods Trees tropical forests
ISSN:	0006-341X, 1541-0420, 1541-0420
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Shrnutí:	We propose a method to test for significant differences in the levels of clustering between two spatial point processes (cases and controls) while taking into account differences in their first-order intensities. The key advance on earlier methods is that the controls are not assumed to be a Poisson process. Inference and diagnostics are based around the inhomogeneous K-function with confidence envelopes obtained from either resampling events in a nonparametric bootstrap approach, or simulating new events as in a parametric bootstrap. Methods developed are demonstrated using the locations of adult and juvenile trees in a tropical forest. A simulation study briefly examines the accuracy and power of the inferential procedures.
Bibliografie:	http://dx.doi.org/10.1111/j.1541-0420.2008.01070.x ark:/67375/WNG-H4NNWH46-L istex:24F420863D754181312E82972F2CD64DBE3ED738 ArticleID:BIOM1070 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
ISSN:	0006-341X 1541-0420 1541-0420
DOI:	10.1111/j.1541-0420.2008.01070.x