Beginner's guide to spatial, temporal and spatial-temporal ecological data analysis with R-INLA
This title consists of two volumes. Volume 2 explains how to apply zero-inflated models and generalised additive (mixed-effects) models to spatial and spatial-temporal data, which is typical of the messy, real-world data obtained by biologists. After explaining how to deal with zero-inflated data, the authors introduce so-called zero-inflated Poisson (ZIP) models, zero-inflated negative binomial (ZINB) models, zero-altered Poisson (ZAP) models and zero-altered negative binomial (ZINB) models, and then extend all these to models with spatial correlation. Examples of datasets analysed include begging behaviour of owl nestlings, sandeel count data, zero-inflated bird densities sampled in the Labrador Sea, coral reef data sampled around an island, and aggregated tornado data in 102 counties in Illinois.
| Main Authors: | , , |
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| Format: | Texto biblioteca |
| Language: | eng |
| Published: |
Newburgh, Scotland Highland Statistics Ltd
2017
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| Subjects: | Modelos lineales (Estadística), Métodos estadísticos, R (Lenguaje de programación para computadora), Ecología, |
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| Summary: | This title consists of two volumes. Volume 2 explains how to apply zero-inflated models and generalised additive (mixed-effects) models to spatial and spatial-temporal data, which is typical of the messy, real-world data obtained by biologists. After explaining how to deal with zero-inflated data, the authors introduce so-called zero-inflated Poisson (ZIP) models, zero-inflated negative binomial (ZINB) models, zero-altered Poisson (ZAP) models and zero-altered negative binomial (ZINB) models, and then extend all these to models with spatial correlation. Examples of datasets analysed include begging behaviour of owl nestlings, sandeel count data, zero-inflated bird densities sampled in the Labrador Sea, coral reef data sampled around an island, and aggregated tornado data in 102 counties in Illinois. |
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