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Bayesian population analysis using WinBUGS : a hierarchical perspective /
Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS and its open-source sister OpenBugs is currently the only flexible and general-purpose program available with which the average ecologist can conduct standa...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Waltham, MA :
Academic Press,
2012.
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| Edición: | 1st ed. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a K�ery, Marc. | |
| 245 | 1 | 0 | |a Bayesian population analysis using WinBUGS : |b a hierarchical perspective / |c Marc Kery and Michael Schaub ; foreword by Steven R. Beissinger. |
| 250 | |a 1st ed. | ||
| 260 | |a Waltham, MA : |b Academic Press, |c 2012. | ||
| 300 | |a 1 online resource (xvii, 535 pages) : |b illustrations (some color) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a data file | ||
| 520 | |a Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS and its open-source sister OpenBugs is currently the only flexible and general-purpose program available with which the average ecologist can conduct standard and non-standard Bayesian statistics. Comprehensive and richly-commented examples illustrate a wide range of models that are most relevant to the research of a modern population ecologist. All WinBUGS/OpenBUGS analyses are completely integrated in software R. Includes complete documentation of all R and WinBUGS code required to conduct analyses and shows all the necessary steps from having the data in a text file out of Excel to interpreting and processing the output from WinBUGS in R. | ||
| 505 | 0 | |a Preface Acknowledgements 1. Introduction 2. Very brief introduction to Bayesian statistical modeling 3. Introduction to the generalized linear model (GLM): The simplest model for count data 4. Introduction to random effects: The conventional Poisson GLMM for count data 5. State-space models 6. Estimation of population size 7. Estimation of survival probabilities using capture-recapture data 8. Estimation of survival probabilities using mark-recovery data 9. Multistate capture-recapture models 10. Estimation of survival and recruitment using the Jolly-Seber model 11. Integrated population models 12. Metapopulation modeling of abundance using hierarchical Poisson regression 13. Metapopulation modeling of species distributions using hierarchical logistic regression 14. Concluding remarks Appendices References. | |
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 546 | |a English. | ||
| 630 | 0 | 0 | |a WinBUGS. |
| 650 | 0 | |a Population biology |x Data processing. | |
| 650 | 2 | |a Bayes Theorem |0 (DNLM)D001499 | |
| 650 | 2 | |a Population Characteristics |0 (DNLM)D011154 | |
| 650 | 2 | |a Textbooks | |
| 650 | 6 | |a Biologie des populations |0 (CaQQLa)201-0062278 |x Informatique. |0 (CaQQLa)201-0380011 | |
| 650 | 6 | |a Th�eor�eme de Bayes. |0 (CaQQLa)000272232 | |
| 650 | 7 | |a NATURE |x Ecology. |2 bisacsh | |
| 650 | 7 | |a NATURE |x Ecosystems & Habitats |x Wilderness. |2 bisacsh | |
| 650 | 7 | |a SCIENCE |x Environmental Science. |2 bisacsh | |
| 650 | 7 | |a SCIENCE |x Life Sciences |x Ecology. |2 bisacsh | |
| 630 | 0 | 7 | |a WinBUGS |2 fast |0 (OCoLC)fst01796027 |
| 650 | 7 | |a Population biology |x Data processing |2 fast |0 (OCoLC)fst01071536 | |
| 650 | 7 | |a Bayes-Verfahren |2 gnd |0 (DE-588)4204326-8 | |
| 650 | 7 | |a Dem�okologie |2 gnd |0 (DE-588)4149059-9 | |
| 650 | 7 | |a Populationsbiologie. |2 idszbz | |
| 650 | 7 | |a Populationsdynamik. |2 idszbz | |
| 650 | 7 | |a Biometrie. |2 idszbz | |
| 650 | 7 | |a Bayes-Entscheidungstheorie. |2 idszbz | |
| 650 | 7 | |a Statistisches Modell. |2 idszbz | |
| 655 | 7 | |a Textbooks |2 fast |0 (OCoLC)fst01423863 | |
| 655 | 7 | |a Textbooks. |2 lcgft | |
| 700 | 1 | |a Schaub, Michael. | |
| 776 | 0 | 8 | |i Print version: |a K�ery, Marc. |t Bayesian population analysis using WinBUGS. |b 1st ed. |d Waltham, MA : Academic Press, 2012 |z 9780123870209 |w (DLC) 2011029641 |w (OCoLC)731925446 |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780123870209 |z Texto completo |