Correction to Koen's critical values in testing spatial randomness

Sung Nok Chiu

doi:10.1080/10629360600989147

Correction to Koen's critical values in testing spatial randomness

Sung Nok Chiu^*

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Journal article › peer-review

4 Citations (Scopus)

23 Downloads (Pure)

Abstract

Using Ripley's K-function in testing spatial randomness, Koen's estimated critical values deviated notably from Ripley's approximation formula; the former, however, came from an incorrect algorithm. This paper reports new estimates, which agree very well with Ripley's approximation and recommends that the approximation formula can be used instead of Monte-Carlo tests.

Original language	English
Pages (from-to)	1001-1004
Number of pages	4
Journal	Journal of Statistical Computation and Simulation
Volume	77
Issue number	11
DOIs	https://doi.org/10.1080/10629360600989147
Publication status	Published - Jan 2007

Scopus Subject Areas

Statistics and Probability
Modelling and Simulation
Statistics, Probability and Uncertainty
Applied Mathematics

User-Defined Keywords

Complete spatial randomness
Spatial point patterns

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10.1080/10629360600989147

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Cite this

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abstract = "Using Ripley's K-function in testing spatial randomness, Koen's estimated critical values deviated notably from Ripley's approximation formula; the former, however, came from an incorrect algorithm. This paper reports new estimates, which agree very well with Ripley's approximation and recommends that the approximation formula can be used instead of Monte-Carlo tests.",

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AB - Using Ripley's K-function in testing spatial randomness, Koen's estimated critical values deviated notably from Ripley's approximation formula; the former, however, came from an incorrect algorithm. This paper reports new estimates, which agree very well with Ripley's approximation and recommends that the approximation formula can be used instead of Monte-Carlo tests.

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Correction to Koen's critical values in testing spatial randomness

Abstract

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