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Beginner's guide to spatial, temporal and spatial-temporal ecological data analysis with R-INLA Alain F. Zuur, Elena N. Ieno, Anatoly A. Saveliev

Tipo de material: Libro
 impreso(a) 
 Libro impreso(a) Idioma: Inglés Detalles de publicación: Newburgh, Scotland Highland Statistics Ltd 2017Edición: First published, 2017 (volumen I); first published, 2018 (volumen II)Descripción: 2 volúmenes fotografías, gráficas, ilustraciones, mapas 23 centímetrosTipo de contenido:
  • Texto
Tipo de medio:
  • Sin medio
Tipo de soporte:
  • Volumen
ISBN:
  • 0957174195
  • 9780957174191 (Volumen I)
  • 9780957174146 (Volumen II)
Tema(s): Clasificación:
  • 519.5 Z8
Resumen:
Inglés

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.

Número de sistema: 59114
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Volumen I. Using GLM and GLMM -- Volumen II. GAM and zero-inflated models

Incluye bibliografía: páginas 347-352 e índice: páginas 353-253

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. Inglés