Chi-squared tests using local inhomogeneous mark-weighted K-functions can identify global and local deviations from null hypotheses in marked point patterns, even with subtle structures or small samples.
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stat.ME 2years
2026 2verdicts
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No single goodness-of-fit or two-sample test reliably detects deviations across all multivariate scenarios, so the authors recommend a small combination of methods that together cover the simulated cases.
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Testing the Structural Properties of Marked Point Processes Using Local Inhomogeneous Mark-Weighted K-Functions
Chi-squared tests using local inhomogeneous mark-weighted K-functions can identify global and local deviations from null hypotheses in marked point patterns, even with subtle structures or small samples.
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Power Studies For Two-Sample and Goodness-of-Fit Methods For Multivariate Data
No single goodness-of-fit or two-sample test reliably detects deviations across all multivariate scenarios, so the authors recommend a small combination of methods that together cover the simulated cases.