Spatial and Spatio-temporal Bayesian Models with R - INLA (PDF)
(Sprache: Englisch)
Spatial and Spatio-Temporal Bayesian Models with
R-INLA provides a much needed, practically oriented
& innovative presentation of the combination of Bayesian
methodology and spatial statistics. The authors combine an
introduction to Bayesian theory and...
R-INLA provides a much needed, practically oriented
& innovative presentation of the combination of Bayesian
methodology and spatial statistics. The authors combine an
introduction to Bayesian theory and...
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Spatial and Spatio-Temporal Bayesian Models with
R-INLA provides a much needed, practically oriented
& innovative presentation of the combination of Bayesian
methodology and spatial statistics. The authors combine an
introduction to Bayesian theory and methodology with a focus on the
spatial and spatio--temporal models used within the Bayesian
framework and a series of practical examples which allow the reader
to link the statistical theory presented to real data problems. The
numerous examples from the fields of epidemiology, biostatistics
and social science all are coded in the R package R-INLA, which has
proven to be a valid alternative to the commonly used Markov Chain
Monte Carlo simulations
R-INLA provides a much needed, practically oriented
& innovative presentation of the combination of Bayesian
methodology and spatial statistics. The authors combine an
introduction to Bayesian theory and methodology with a focus on the
spatial and spatio--temporal models used within the Bayesian
framework and a series of practical examples which allow the reader
to link the statistical theory presented to real data problems. The
numerous examples from the fields of epidemiology, biostatistics
and social science all are coded in the R package R-INLA, which has
proven to be a valid alternative to the commonly used Markov Chain
Monte Carlo simulations
Autoren-Porträt von Marta Blangiardo, Michela Cameletti
Marta Blangiardo, MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, UKMichela Cameletti, Department of Management, Economics and Quantitative Methods, University of Bergamo, Italy
Bibliographische Angaben
- Autoren: Marta Blangiardo , Michela Cameletti
- 2015, 1. Auflage, 320 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 1118950216
- ISBN-13: 9781118950210
- Erscheinungsdatum: 26.03.2015
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Größe: 26 MB
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Englisch
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