Leverage and influence diagnostics for Gibbs spatial point processes
For point process models fitted to spatial point pattern data, we describe diagnostic quantities analogous to the classical regression diagnostics of leverage and influence. We develop a simple and accessible approach to these diagnostics, and use it to extend previous results for Poisson point proc...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | English |
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ELSEVIER SCI LTD
2019
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| Subjects: | |
| Online Access: | http://purl.org/au-research/grants/arc/DP130104470 http://hdl.handle.net/20.500.11937/90993 |
| _version_ | 1848765480319320064 |
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| author | Baddeley, Adrian Rubak, E. Turner, R. |
| author_facet | Baddeley, Adrian Rubak, E. Turner, R. |
| author_sort | Baddeley, Adrian |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | For point process models fitted to spatial point pattern data, we describe diagnostic quantities analogous to the classical regression diagnostics of leverage and influence. We develop a simple and accessible approach to these diagnostics, and use it to extend previous results for Poisson point process models to the vastly larger class of Gibbs point processes. Explicit expressions, and efficient calculation formulae, are obtained for models fitted by maximum pseudolikelihood, maximum logistic composite likelihood, and regularised composite likelihoods. For practical applications we introduce new graphical tools, and a new diagnostic analogous to the effect measure DFFIT in regression. |
| first_indexed | 2025-11-14T11:35:55Z |
| format | Journal Article |
| id | curtin-20.500.11937-90993 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:35:55Z |
| publishDate | 2019 |
| publisher | ELSEVIER SCI LTD |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-909932023-06-13T02:53:44Z Leverage and influence diagnostics for Gibbs spatial point processes Baddeley, Adrian Rubak, E. Turner, R. Science & Technology Physical Sciences Technology Geosciences, Multidisciplinary Mathematics, Interdisciplinary Applications Remote Sensing Statistics & Probability Geology Mathematics Composite likelihood Conditional intensity DFBETA DFFIT Model validation Pseudolikelihood CASE-DELETION DIAGNOSTICS LOGISTIC-REGRESSION MODEL For point process models fitted to spatial point pattern data, we describe diagnostic quantities analogous to the classical regression diagnostics of leverage and influence. We develop a simple and accessible approach to these diagnostics, and use it to extend previous results for Poisson point process models to the vastly larger class of Gibbs point processes. Explicit expressions, and efficient calculation formulae, are obtained for models fitted by maximum pseudolikelihood, maximum logistic composite likelihood, and regularised composite likelihoods. For practical applications we introduce new graphical tools, and a new diagnostic analogous to the effect measure DFFIT in regression. 2019 Journal Article http://hdl.handle.net/20.500.11937/90993 10.1016/j.spasta.2018.09.004 English http://purl.org/au-research/grants/arc/DP130104470 ELSEVIER SCI LTD fulltext |
| spellingShingle | Science & Technology Physical Sciences Technology Geosciences, Multidisciplinary Mathematics, Interdisciplinary Applications Remote Sensing Statistics & Probability Geology Mathematics Composite likelihood Conditional intensity DFBETA DFFIT Model validation Pseudolikelihood CASE-DELETION DIAGNOSTICS LOGISTIC-REGRESSION MODEL Baddeley, Adrian Rubak, E. Turner, R. Leverage and influence diagnostics for Gibbs spatial point processes |
| title | Leverage and influence diagnostics for Gibbs spatial point processes |
| title_full | Leverage and influence diagnostics for Gibbs spatial point processes |
| title_fullStr | Leverage and influence diagnostics for Gibbs spatial point processes |
| title_full_unstemmed | Leverage and influence diagnostics for Gibbs spatial point processes |
| title_short | Leverage and influence diagnostics for Gibbs spatial point processes |
| title_sort | leverage and influence diagnostics for gibbs spatial point processes |
| topic | Science & Technology Physical Sciences Technology Geosciences, Multidisciplinary Mathematics, Interdisciplinary Applications Remote Sensing Statistics & Probability Geology Mathematics Composite likelihood Conditional intensity DFBETA DFFIT Model validation Pseudolikelihood CASE-DELETION DIAGNOSTICS LOGISTIC-REGRESSION MODEL |
| url | http://purl.org/au-research/grants/arc/DP130104470 http://hdl.handle.net/20.500.11937/90993 |