| | Accession Number | 5004893 |
| | Title | Hierarchical models for estimation of population parameters |
| | Project Description | Hierarchical models for estimation of population parameters Project status: Active Start date: |
| | 011001 End date: 061001 Wildlife management and ecological research are increasingly guided |
| | by analyses of large and complex datasets. The description of such datasets often requires a |
| | large number of parameters, among which certain patterns might be discernible. For example, one |
| | may consider a long-term study producing estimates of annual survival rates; of interest is the |
| | question whether these rates have declined through time. Several statistical methods exist for |
| | examining pattern in collections of parameters. Random effects models, in which parameters are |
| | regarded as random variables, with distributions governed by "hyperparameters" are required for |
| | describing the patterns of interest. Unfortunately, implementation of random effects models is |
| | sometimes difficult. Ultrastructural models, in which the postulated pattern is built into the |
| | parameter structure of the original data analysis, are approximations to random effects models. |
| | However, this approximation is not completely satisfactory: failure to account for natural variation |
| | among parameters can lead to overstatement of the evidence for pattern among parameters. |
| | Quasi-likelihood methods can be used to improve the approximation of random effects models by |
| | ultrastructural models, but frequently lack a firm mathematical foundation and hence produce |
| | inferences of dubious merit. This study investigates the use of Bayesian hierarchical models, and |
| | Markov Chain Monte Carlo methods, to a wide variety of wildlife and ecological problems, including |
| | capture-recapture models and demographic analysis. |
| | Keywords | bayesian inference, estimation, hierarchical modeling, markov chain monte carlo, |
| | Principal | William A Link, USGS Patuxent Wildlife Research Center: william_link@usgs.gov; |
| | Investigators |
Return to SIS Projects Listing
