Testing uniformity of a spatial point pattern

Lai Ping Ho*, Sung Nok Chiu

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

8 Citations (Scopus)
53 Downloads (Pure)

Abstract

For a spatial point pattern observed in a bounded window, we propose using discrepancies, which are measures of uniformity in the quasi-Monte Carlo method, to test the complete spatial randomness hypothesis. Tests using these discrepancies are in fact goodness-of-fit tests for uniform distribution. The discrepancies are free from edge effects and, unlike the popular maximum absolute pointwise difference statistic of a summary function over a suitably chosen range, do not have an arbitrary parameter. Simulation studies show that they are often more powerful when a given pattern is a realization of a process with long-range interaction or a nonstationary process.

Original languageEnglish
Pages (from-to)378-398
Number of pages21
JournalJournal of Computational and Graphical Statistics
Volume16
Issue number2
DOIs
Publication statusPublished - Jun 2007

Scopus Subject Areas

  • Statistics and Probability
  • Discrete Mathematics and Combinatorics
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • Complete spatial randomness
  • Discrepancy
  • Quasi-Monte Carlo method
  • Spatial point process

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