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
Biometricsjournal_title
Biometricsauthors
He Z,Sun Ddoi
10.1111/j.0006-341x.2000.00360.xsubject
Has Abstractpub_date
2000-06-01 00:00:00pages
360-7issue
2eissn
0006-341Xissn
1541-0420journal_volume
56pub_type
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