Hierarchical Bayes estimation of hunting success rates with spatial correlations.

Abstract:

:A Bayesian hierarchical generalized linear model is used to estimate hunting success rates at the subarea level for postseason harvest surveys. The model includes fixed week effects, random geographic effects, and spatial correlations between neighboring subareas. The computation is done by Gibbs sampling and adaptive rejection sampling techniques. The method is illustrated using data from the Missouri Turkey Hunting Survey in the spring of 1996. Bayesian model selection methods are used to demonstrate that there are significant week differences and spatial correlations of hunting success rates among counties. The Bayesian estimates are also shown to be quite robust in terms of changes of hyperparameters.

journal_name

Biometrics

journal_title

Biometrics

authors

He Z,Sun D

doi

10.1111/j.0006-341x.2000.00360.x

subject

Has Abstract

pub_date

2000-06-01 00:00:00

pages

360-7

issue

2

eissn

0006-341X

issn

1541-0420

journal_volume

56

pub_type

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