Illian, J. B. , Sørbye, S. H., Rue, H. and Hendrichsen, D. K. (2012) Using INLA to fit a complex point process model with temporally varying effects - a case study. Journal of Environmental Statistics, 3(7),
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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.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Illian, Professor Janine |
Authors: | Illian, J. B., Sørbye, S. H., Rue, H., and Hendrichsen, D. K. |
College/School: | College of Science and Engineering > School of Mathematics and Statistics > Statistics |
Journal Name: | Journal of Environmental Statistics |
Publisher: | UCLA Statistics |
ISSN: | 1945-1296 |
ISSN (Online): | 1945-1296 |
Copyright Holders: | Copyright © 2012 The Authors |
First Published: | First published in Journal of Environmental Studies 3:7 |
Publisher Policy: | Reproduced under a Creative Commons License |
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