Document Type

Journal Article

Department/Unit

Department of Mathematics

Language

English

Abstract

A very common way of analyzing different and complicated plant behaviors is to use spatial point pattern analysis, which allows us to assess whether there is any structure present. To test the complete spatial randomness hypothesis, Diggle (1979Diggle , P. J. ( 1979 ). On parameter estimation and goodness-of-fit testing for spatial point patterns . Biometrics 35 : 87 – 101 .[CrossRef], [Web of Science ®], [Google Scholar]) proposed a Monte Carlo test whose test statistic is the discrepancy between the estimated and the theoretical form of some summary function, such as the Ripley K-function. In this article, we improve this test by adding various weight functions and get more powerful tests if decreasing and increasing weight functions are used for processes with short and long, respectively, range of interaction.

Keywords

Complete spatial randomness, Edge-correction, K-function, Monte Carlo simulation

Publication Date

12-22-2008

Source Publication Title

Communications in Statistics - Simulation and Computation

Volume

38

Issue

2

Start Page

269

End Page

287

Publisher

Taylor & Francis

Peer Reviewed

1

Copyright

This is an Accepted Manuscript of an article published by Taylor & Francis in Communications in Statistics - Simulation and Computation in January 2009, available online: http://dx.doi.org/10.1080/03610910802478343.

Funder

This research was supported by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project Nos. HKBU2048/02P and HKBU200503) and an FRG grant of the Hong Kong Baptist University.

DOI

10.1080/03610910802478343

Link to Publisher's Edition

http://dx.doi.org/10.1080/03610910802478343

ISSN (print)

03610918

ISSN (electronic)

15324141

Included in

Mathematics Commons

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