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...
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ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/3306 2023-07-02T03:32:26+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 University of St Andrews. School of Mathematics and Statistics University of St Andrews. Scottish Oceans Institute University of St Andrews. Centre for Research into Ecological & Environmental Modelling 2012-12-17T16:01:01Z application/pdf http://hdl.handle.net/10023/3306 http://www.math.ntnu.no/inla/r-inla.org/papers/S17-2010.pdf http://www.jenvstat.org/v03/i07/paper eng eng Journal of Environmental Statistics 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 . 1945-1296 PURE: 5264614 PURE UUID: 72fb0cdc-7829-4e28-9327-2b419a624ed7 http://hdl.handle.net/10023/3306 http://www.math.ntnu.no/inla/r-inla.org/papers/S17-2010.pdf http://www.jenvstat.org/v03/i07/paper (c) 2012 The authors. This is an open access article available under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) which permits anyone to download, reuse, reprint, modify, distribute, and/or copy articles in Journal of Environmental Statistics, so long as the original authors and source are credited. Spatial point process Spatial scale Replicated patterns QA Mathematics QA Journal article 2012 ftstandrewserep 2023-06-13T18:30:54Z 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. Publisher PDF Peer reviewed Article in Journal/Newspaper Greenland ovibos moschatus Zackenberg University of St Andrews: Digital Research Repository Greenland Laplace ENVELOPE(141.467,141.467,-66.782,-66.782) |
institution |
Open Polar |
collection |
University of St Andrews: Digital Research Repository |
op_collection_id |
ftstandrewserep |
language |
English |
topic |
Spatial point process Spatial scale Replicated patterns QA Mathematics QA |
spellingShingle |
Spatial point process Spatial scale Replicated patterns QA Mathematics QA 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 QA Mathematics QA |
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. Publisher PDF Peer reviewed |
author2 |
University of St Andrews. School of Mathematics and Statistics University of St Andrews. Scottish Oceans Institute University of St Andrews. Centre for Research into Ecological & Environmental Modelling |
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 |
http://hdl.handle.net/10023/3306 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_relation |
Journal of Environmental Statistics 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 . 1945-1296 PURE: 5264614 PURE UUID: 72fb0cdc-7829-4e28-9327-2b419a624ed7 http://hdl.handle.net/10023/3306 http://www.math.ntnu.no/inla/r-inla.org/papers/S17-2010.pdf http://www.jenvstat.org/v03/i07/paper |
op_rights |
(c) 2012 The authors. This is an open access article available under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) which permits anyone to download, reuse, reprint, modify, distribute, and/or copy articles in Journal of Environmental Statistics, so long as the original authors and source are credited. |
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