Using INLA to fit a complex point process model with temporally varying effects – a case study
Integrated nested Laplace approximation (INLA) provides a fast and yet quite exact approach to fitting complex latent Gaussian models which comprise many statistical models in a Bayesian context, including log Gaussian Cox processes. This paper discusses how a joint log Gaussian Cox process model ma...
Main Authors: | , , , |
---|---|
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2012
|
Subjects: | |
Online Access: | https://risweb.st-andrews.ac.uk/portal/en/researchoutput/using-inla-to-fit-a-complex-point-process-model-with-temporally-varying-effects--a-case-study(72fb0cdc-7829-4e28-9327-2b419a624ed7).html https://research-repository.st-andrews.ac.uk/bitstream/10023/3306/1/JES_Illian_et_al.pdf http://www.math.ntnu.no/inla/r-inla.org/papers/S17-2010.pdf http://www.jenvstat.org/v03/i07/paper |
id |
ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/72fb0cdc-7829-4e28-9327-2b419a624ed7 |
---|---|
record_format |
openpolar |
spelling |
ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/72fb0cdc-7829-4e28-9327-2b419a624ed7 2023-05-15T16:28:47+02:00 Using INLA to fit a complex point process model with temporally varying effects – a case study Illian, Janine Baerbel Soerbye, S Rue, H Hendrichsen, D 2012-07 application/pdf https://risweb.st-andrews.ac.uk/portal/en/researchoutput/using-inla-to-fit-a-complex-point-process-model-with-temporally-varying-effects--a-case-study(72fb0cdc-7829-4e28-9327-2b419a624ed7).html https://research-repository.st-andrews.ac.uk/bitstream/10023/3306/1/JES_Illian_et_al.pdf http://www.math.ntnu.no/inla/r-inla.org/papers/S17-2010.pdf http://www.jenvstat.org/v03/i07/paper eng eng info:eu-repo/semantics/openAccess Illian , J B , Soerbye , S , Rue , H & Hendrichsen , D 2012 , ' Using INLA to fit a complex point process model with temporally varying effects – a case study ' , Journal of Environmental Statistics , vol. 3 , no. 7 . Spatial point process Spatial scale Replicated patterns article 2012 ftunstandrewcris 2021-12-26T14:19:04Z Integrated nested Laplace approximation (INLA) provides a fast and yet quite exact approach to fitting complex latent Gaussian models which comprise many statistical models in a Bayesian context, including log Gaussian Cox processes. This paper discusses how a joint log Gaussian Cox process model may be fitted to independent replicated point patterns. We illustrate the approach by fitting a model to data on the locations of muskoxen (Ovibos moschatus) herds in Zackenberg valley, Northeast Greenland and by detailing how this model is specified within the R-interface R-INLA. The paper strongly focuses on practical problems involved in the modelling process, including issues of spatial scale, edge effects and prior choices, and finishes with a discussion on models with varying boundary conditions. Article in Journal/Newspaper Greenland ovibos moschatus Zackenberg University of St Andrews: Research Portal Greenland Laplace ENVELOPE(141.467,141.467,-66.782,-66.782) |
institution |
Open Polar |
collection |
University of St Andrews: Research Portal |
op_collection_id |
ftunstandrewcris |
language |
English |
topic |
Spatial point process Spatial scale Replicated patterns |
spellingShingle |
Spatial point process Spatial scale Replicated patterns Illian, Janine Baerbel Soerbye, S Rue, H Hendrichsen, D Using INLA to fit a complex point process model with temporally varying effects – a case study |
topic_facet |
Spatial point process Spatial scale Replicated patterns |
description |
Integrated nested Laplace approximation (INLA) provides a fast and yet quite exact approach to fitting complex latent Gaussian models which comprise many statistical models in a Bayesian context, including log Gaussian Cox processes. This paper discusses how a joint log Gaussian Cox process model may be fitted to independent replicated point patterns. We illustrate the approach by fitting a model to data on the locations of muskoxen (Ovibos moschatus) herds in Zackenberg valley, Northeast Greenland and by detailing how this model is specified within the R-interface R-INLA. The paper strongly focuses on practical problems involved in the modelling process, including issues of spatial scale, edge effects and prior choices, and finishes with a discussion on models with varying boundary conditions. |
format |
Article in Journal/Newspaper |
author |
Illian, Janine Baerbel Soerbye, S Rue, H Hendrichsen, D |
author_facet |
Illian, Janine Baerbel Soerbye, S Rue, H Hendrichsen, D |
author_sort |
Illian, Janine Baerbel |
title |
Using INLA to fit a complex point process model with temporally varying effects – a case study |
title_short |
Using INLA to fit a complex point process model with temporally varying effects – a case study |
title_full |
Using INLA to fit a complex point process model with temporally varying effects – a case study |
title_fullStr |
Using INLA to fit a complex point process model with temporally varying effects – a case study |
title_full_unstemmed |
Using INLA to fit a complex point process model with temporally varying effects – a case study |
title_sort |
using inla to fit a complex point process model with temporally varying effects – a case study |
publishDate |
2012 |
url |
https://risweb.st-andrews.ac.uk/portal/en/researchoutput/using-inla-to-fit-a-complex-point-process-model-with-temporally-varying-effects--a-case-study(72fb0cdc-7829-4e28-9327-2b419a624ed7).html https://research-repository.st-andrews.ac.uk/bitstream/10023/3306/1/JES_Illian_et_al.pdf http://www.math.ntnu.no/inla/r-inla.org/papers/S17-2010.pdf http://www.jenvstat.org/v03/i07/paper |
long_lat |
ENVELOPE(141.467,141.467,-66.782,-66.782) |
geographic |
Greenland Laplace |
geographic_facet |
Greenland Laplace |
genre |
Greenland ovibos moschatus Zackenberg |
genre_facet |
Greenland ovibos moschatus Zackenberg |
op_source |
Illian , J B , Soerbye , S , Rue , H & Hendrichsen , D 2012 , ' Using INLA to fit a complex point process model with temporally varying effects – a case study ' , Journal of Environmental Statistics , vol. 3 , no. 7 . |
op_rights |
info:eu-repo/semantics/openAccess |
_version_ |
1766018457207308288 |