A Bayesian hierarchical model for over-dispersed count data: A case study for abundance of hake recruits

Jorge M. Mendes; K. F. Turkman; Ernesto Jardim

doi:10.1002/env.800

A Bayesian hierarchical model for over-dispersed count data: A case study for abundance of hake recruits

Jorge M. Mendes, K. F. Turkman, Ernesto Jardim

NOVA Information Management School (NOVA IMS)

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4 Citations (Scopus)

Abstract

In this paper, we introduce a Bayesian Hierarchical model to estimate the abundance of hake recruits, as well as to study their spatial distributional patterns in the Portuguese territorial waters. Main objective of the paper is to improve on traditional empirical methods based on sampling averages and variances by using probabilistic models that capture spatial dependence structures.

Original language	English
Pages (from-to)	27-53
Number of pages	27
Journal	Environmetrics
Volume	18
Issue number	1
DOIs	https://doi.org/10.1002/env.800
Publication status	Published - Feb 2007

Keywords

Abundance index
Bayesian hierarchical models
Gibbs sampling
Hake recruitment
MCMC
Over-dispersed count data

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10.1002/env.800

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abstract = "In this paper, we introduce a Bayesian Hierarchical model to estimate the abundance of hake recruits, as well as to study their spatial distributional patterns in the Portuguese territorial waters. Main objective of the paper is to improve on traditional empirical methods based on sampling averages and variances by using probabilistic models that capture spatial dependence structures.",

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KW - Hake recruitment

KW - MCMC

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A Bayesian hierarchical model for over-dispersed count data: A case study for abundance of hake recruits

Abstract

Keywords

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