Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack?Jolly?Seber model
Environmental and Ecological Statistics
DOI 10.1007/s10651-007-0037-9 6893_Link.pdf
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Abstract
Judicious choice of candidate generating distributions improves efficiency of the Metropolis-Hastings algorithm. In Bayesian applications, it is sometimes possible to identify an approximation to the target posterior distribution; this approximate posterior distribution is a good choice for candidate generation. These observations are applied to analysis of the Cormack?Jolly?Seber model and its extensions.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack?Jolly?Seber model |
| Series title | Environmental and Ecological Statistics |
| Volume | 15 |
| Year Published | 2008 |
| Language | English |
| Contributing office(s) | Patuxent Wildlife Research Center |
| Description | 79-87 |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Environmental and Ecological Statistics |
| First page | 79 |
| Last page | 87 |