On the Bayesian analysis of ring-recovery data

被引:41
作者
Brooks, SP [1 ]
Catchpole, EA
Morgan, BJT
Barry, SC
机构
[1] Univ Surrey, Dept Math & Stat, Guildford GU2 5XH, Surrey, England
[2] Univ Coll UNSW, Sch Math & Stat, Australian Def Force Acad, Canberra, ACT 2600, Australia
[3] Univ Kent, Inst Math & Stat, Canterbury CT2 7NF, Kent, England
[4] Australian Natl Univ, Dept Stat & Econometr, Canberra, ACT 0200, Australia
关键词
Bayesian inference; herring gulls; mallards; marginal inference; Markov chain Monte Carlo; maximum likelihood; ridge; ring-recovery data;
D O I
10.1111/j.0006-341X.2000.00951.x
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Vounatsou and Smith (1995, Biometrics 51, 687-708) describe the modern Bayesian analysis of ring-recovery data. Here we discuss and extend their work. We draw different conclusions from two major data analyses. We emphasize the extreme sensitivity of certain parameter estimates to the choice of prior distribution and conclude that naive use of Bayesian methods in this area can be misleading. Additionally, we explain the discrepancy between the Bayesian and classical analyses when the likelihood surface has a flat ridge; In this case, when there is no unique maximum likelihood estimate, the Bayesian estimators are remarkably precise.
引用
收藏
页码:951 / 956
页数:6
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