Putting It Together: Fitting a Dynamic Model
Abstract The chapter “Putting It Together: Fitting a Dynamic Model” provides a synthesis of the material presented in the book, by presenting a worked example that embraces concepts of density dependence, complex model dynamics, parameter estimation, and model selection using the Akaike information...
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croxfordunivpr:10.1093/oso/9780192843470.003.0017 2024-09-09T19:35:35+00:00 Putting It Together: Fitting a Dynamic Model Essington, Timothy E. 2021 http://dx.doi.org/10.1093/oso/9780192843470.003.0017 https://academic.oup.com/book/chapter-pdf/58466092/oso-9780192843470-chapter-17.pdf en eng Oxford University PressOxford Introduction to Quantitative Ecology page 283-294 ISBN 0192843478 9780192843470 9780191926112 book-chapter 2021 croxfordunivpr https://doi.org/10.1093/oso/9780192843470.003.0017 2024-07-22T04:23:12Z Abstract The chapter “Putting It Together: Fitting a Dynamic Model” provides a synthesis of the material presented in the book, by presenting a worked example that embraces concepts of density dependence, complex model dynamics, parameter estimation, and model selection using the Akaike information criterion. The example chosen is the recovery of gray wolf (Canis lupus) population in Washington State since 2008. The chapter begins by explaining how to fit an observation error model. Next, it examines how to fit a process error model. It then discusses parameter estimates and model selection. The chapter concludes with discussion of how to determine whether the population given as an example exhibits complex population dynamics. Book Part Canis lupus gray wolf Oxford University Press 283 294 |
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Open Polar |
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Oxford University Press |
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croxfordunivpr |
language |
English |
description |
Abstract The chapter “Putting It Together: Fitting a Dynamic Model” provides a synthesis of the material presented in the book, by presenting a worked example that embraces concepts of density dependence, complex model dynamics, parameter estimation, and model selection using the Akaike information criterion. The example chosen is the recovery of gray wolf (Canis lupus) population in Washington State since 2008. The chapter begins by explaining how to fit an observation error model. Next, it examines how to fit a process error model. It then discusses parameter estimates and model selection. The chapter concludes with discussion of how to determine whether the population given as an example exhibits complex population dynamics. |
format |
Book Part |
author |
Essington, Timothy E. |
spellingShingle |
Essington, Timothy E. Putting It Together: Fitting a Dynamic Model |
author_facet |
Essington, Timothy E. |
author_sort |
Essington, Timothy E. |
title |
Putting It Together: Fitting a Dynamic Model |
title_short |
Putting It Together: Fitting a Dynamic Model |
title_full |
Putting It Together: Fitting a Dynamic Model |
title_fullStr |
Putting It Together: Fitting a Dynamic Model |
title_full_unstemmed |
Putting It Together: Fitting a Dynamic Model |
title_sort |
putting it together: fitting a dynamic model |
publisher |
Oxford University PressOxford |
publishDate |
2021 |
url |
http://dx.doi.org/10.1093/oso/9780192843470.003.0017 https://academic.oup.com/book/chapter-pdf/58466092/oso-9780192843470-chapter-17.pdf |
genre |
Canis lupus gray wolf |
genre_facet |
Canis lupus gray wolf |
op_source |
Introduction to Quantitative Ecology page 283-294 ISBN 0192843478 9780192843470 9780191926112 |
op_doi |
https://doi.org/10.1093/oso/9780192843470.003.0017 |
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283 |
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294 |
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1809904951019700224 |