Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models

We develop new tools for formal inference and informal model validation in the analysis of spatial point pattern data. The score test is generalized to a “pseudo-score” test derived from Besag’s pseudo-likelihood, and to a class of diagnostics based on point process residuals. The results lend theor...

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Main Authors: Baddeley, Adrian, Rubak, E., Moller, J.
Format: Journal Article
Published: INST MATHEMATICAL STATISTICS 2011
Online Access:http://hdl.handle.net/20.500.11937/7596
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author Baddeley, Adrian
Rubak, E.
Moller, J.
author_facet Baddeley, Adrian
Rubak, E.
Moller, J.
author_sort Baddeley, Adrian
building Curtin Institutional Repository
collection Online Access
description We develop new tools for formal inference and informal model validation in the analysis of spatial point pattern data. The score test is generalized to a “pseudo-score” test derived from Besag’s pseudo-likelihood, and to a class of diagnostics based on point process residuals. The results lend theoretical support to the established practice of using functional summary statistics, such as Ripley’s K-function, when testing for complete spatial randomness; and they provide new tools such as the compensator of the K-function for testing other fitted models. The results also support localization methods such as the scan statistic and smoothed residual plots. Software for computing the diagnostics is provided.
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format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T06:16:59Z
publishDate 2011
publisher INST MATHEMATICAL STATISTICS
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spelling curtin-20.500.11937-75962017-09-13T14:37:00Z Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models Baddeley, Adrian Rubak, E. Moller, J. We develop new tools for formal inference and informal model validation in the analysis of spatial point pattern data. The score test is generalized to a “pseudo-score” test derived from Besag’s pseudo-likelihood, and to a class of diagnostics based on point process residuals. The results lend theoretical support to the established practice of using functional summary statistics, such as Ripley’s K-function, when testing for complete spatial randomness; and they provide new tools such as the compensator of the K-function for testing other fitted models. The results also support localization methods such as the scan statistic and smoothed residual plots. Software for computing the diagnostics is provided. 2011 Journal Article http://hdl.handle.net/20.500.11937/7596 10.1214/11-STS367 INST MATHEMATICAL STATISTICS unknown
spellingShingle Baddeley, Adrian
Rubak, E.
Moller, J.
Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models
title Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models
title_full Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models
title_fullStr Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models
title_full_unstemmed Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models
title_short Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models
title_sort score, pseudo-score and residual diagnostics for spatial point process models
url http://hdl.handle.net/20.500.11937/7596