Bias correction for parameter estimates of spatial point process models
When a spatial point process model is fitted to spatial point pattern data using standard software, the parameter estimates are typically biased. Contrary to folklore, the bias does not reflect weaknesses of the underlying mathematical methods, but is mainly due to the effects of discretization of t...
| Main Authors: | , |
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| Format: | Journal Article |
| Published: |
TAYLOR & FRANCIS LTD
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/15152 |
| _version_ | 1848748816190144512 |
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| author | Baddeley, Adrian Turner, R. |
| author_facet | Baddeley, Adrian Turner, R. |
| author_sort | Baddeley, Adrian |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | When a spatial point process model is fitted to spatial point pattern data using standard software, the parameter estimates are typically biased. Contrary to folklore, the bias does not reflect weaknesses of the underlying mathematical methods, but is mainly due to the effects of discretization of the spatial domain. We investigate two approaches to correcting the bias: a Newton–Raphson-type correction and Richardson extrapolation. In simulation experiments, Richardson extrapolation performs best. |
| first_indexed | 2025-11-14T07:11:03Z |
| format | Journal Article |
| id | curtin-20.500.11937-15152 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:11:03Z |
| publishDate | 2014 |
| publisher | TAYLOR & FRANCIS LTD |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-151522017-09-13T15:04:06Z Bias correction for parameter estimates of spatial point process models Baddeley, Adrian Turner, R. When a spatial point process model is fitted to spatial point pattern data using standard software, the parameter estimates are typically biased. Contrary to folklore, the bias does not reflect weaknesses of the underlying mathematical methods, but is mainly due to the effects of discretization of the spatial domain. We investigate two approaches to correcting the bias: a Newton–Raphson-type correction and Richardson extrapolation. In simulation experiments, Richardson extrapolation performs best. 2014 Journal Article http://hdl.handle.net/20.500.11937/15152 10.1080/00949655.2012.755976 TAYLOR & FRANCIS LTD restricted |
| spellingShingle | Baddeley, Adrian Turner, R. Bias correction for parameter estimates of spatial point process models |
| title | Bias correction for parameter estimates of spatial point process models |
| title_full | Bias correction for parameter estimates of spatial point process models |
| title_fullStr | Bias correction for parameter estimates of spatial point process models |
| title_full_unstemmed | Bias correction for parameter estimates of spatial point process models |
| title_short | Bias correction for parameter estimates of spatial point process models |
| title_sort | bias correction for parameter estimates of spatial point process models |
| url | http://hdl.handle.net/20.500.11937/15152 |