Autoregressive models for capture-recapture data: A Bayesian approach
In this paper, we incorporate an autoregressive time-series framework into models for animal survival using capture-recapture data. Researchers modelling animal survival probabilities as the realization of a random process have typically considered survival to be independent from one time period to...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.332.388 2023-05-15T13:24:48+02:00 Autoregressive models for capture-recapture data: A Bayesian approach Devin S. Johnson Jennifer A. Hoeting The Pennsylvania State University CiteSeerX Archives 2003 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.388 http://www.stat.colostate.edu/~nsu/starmap/pps/Technical Reports/Johnson.Hoeting.Report.2001.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.388 http://www.stat.colostate.edu/~nsu/starmap/pps/Technical Reports/Johnson.Hoeting.Report.2001.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.stat.colostate.edu/~nsu/starmap/pps/Technical Reports/Johnson.Hoeting.Report.2001.pdf Key words Autoregressive models Bayesian inference MCMC Survival text 2003 ftciteseerx 2016-09-11T00:03:49Z In this paper, we incorporate an autoregressive time-series framework into models for animal survival using capture-recapture data. Researchers modelling animal survival probabilities as the realization of a random process have typically considered survival to be independent from one time period to the next. This may not be realistic for some populations. Using a Gibbs sampling approach we can estimate covariate coefficients and autoregressive parameters for survival models. The procedure is illustrated with a waterfowl band recovery dataset on Northern Pintails (Anas acuta). The analysis shows that the second lag autoregressive coefficient is significantly less than 0, suggesting that there is a triennial relationship between survival probabilities and emphasizing that modelling survival rates as independent random variables may be unrealistic in some cases. Software to implement the methodology is available at no charge on the internet. Text Anas acuta Unknown |
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Key words Autoregressive models Bayesian inference MCMC Survival |
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Key words Autoregressive models Bayesian inference MCMC Survival Devin S. Johnson Jennifer A. Hoeting Autoregressive models for capture-recapture data: A Bayesian approach |
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Key words Autoregressive models Bayesian inference MCMC Survival |
description |
In this paper, we incorporate an autoregressive time-series framework into models for animal survival using capture-recapture data. Researchers modelling animal survival probabilities as the realization of a random process have typically considered survival to be independent from one time period to the next. This may not be realistic for some populations. Using a Gibbs sampling approach we can estimate covariate coefficients and autoregressive parameters for survival models. The procedure is illustrated with a waterfowl band recovery dataset on Northern Pintails (Anas acuta). The analysis shows that the second lag autoregressive coefficient is significantly less than 0, suggesting that there is a triennial relationship between survival probabilities and emphasizing that modelling survival rates as independent random variables may be unrealistic in some cases. Software to implement the methodology is available at no charge on the internet. |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Devin S. Johnson Jennifer A. Hoeting |
author_facet |
Devin S. Johnson Jennifer A. Hoeting |
author_sort |
Devin S. Johnson |
title |
Autoregressive models for capture-recapture data: A Bayesian approach |
title_short |
Autoregressive models for capture-recapture data: A Bayesian approach |
title_full |
Autoregressive models for capture-recapture data: A Bayesian approach |
title_fullStr |
Autoregressive models for capture-recapture data: A Bayesian approach |
title_full_unstemmed |
Autoregressive models for capture-recapture data: A Bayesian approach |
title_sort |
autoregressive models for capture-recapture data: a bayesian approach |
publishDate |
2003 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.388 http://www.stat.colostate.edu/~nsu/starmap/pps/Technical Reports/Johnson.Hoeting.Report.2001.pdf |
genre |
Anas acuta |
genre_facet |
Anas acuta |
op_source |
http://www.stat.colostate.edu/~nsu/starmap/pps/Technical Reports/Johnson.Hoeting.Report.2001.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.388 http://www.stat.colostate.edu/~nsu/starmap/pps/Technical Reports/Johnson.Hoeting.Report.2001.pdf |
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Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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