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Using INLA to fit a complex point process model with temporally varying effects – a case study
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dc.contributor.author | Illian, Janine Baerbel | |
dc.contributor.author | Soerbye, S | |
dc.contributor.author | Rue, H | |
dc.contributor.author | Hendrichsen, D | |
dc.date.accessioned | 2012-12-17T16:01:01Z | |
dc.date.available | 2012-12-17T16:01:01Z | |
dc.date.issued | 2012-07 | |
dc.identifier.citation | 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 . | en |
dc.identifier.issn | 1945-1296 | |
dc.identifier.other | PURE: 5264614 | |
dc.identifier.other | PURE UUID: 72fb0cdc-7829-4e28-9327-2b419a624ed7 | |
dc.identifier.uri | https://hdl.handle.net/10023/3306 | |
dc.description.abstract | 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. | |
dc.language.iso | eng | |
dc.relation.ispartof | Journal of Environmental Statistics | en |
dc.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. | en |
dc.subject | Spatial point process | en |
dc.subject | Spatial scale | en |
dc.subject | Replicated patterns | en |
dc.subject | QA Mathematics | en |
dc.subject.lcc | QA | en |
dc.title | Using INLA to fit a complex point process model with temporally varying effects – a case study | en |
dc.type | Journal article | en |
dc.description.version | Publisher PDF | en |
dc.contributor.institution | University of St Andrews. School of Mathematics and Statistics | en |
dc.contributor.institution | University of St Andrews. Scottish Oceans Institute | en |
dc.contributor.institution | University of St Andrews. Centre for Research into Ecological & Environmental Modelling | en |
dc.description.status | Peer reviewed | en |
dc.identifier.url | http://www.math.ntnu.no/inla/r-inla.org/papers/S17-2010.pdf | en |
dc.identifier.url | http://www.jenvstat.org/v03/i07/paper | en |
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