9781032092416 - bringing bayesian models to life di hooten, mevin b.; hefley, trevor (21 risultati)

Lingua: Inglese
Editore: CRC Press, 2021
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Altre immaginiLingua: Inglese
Editore: CRC Press, 2021
Serie: Chapman & Hall/CRC Applied Environmental Statistics, Libro 10 di 15. Libro 10 di 15 - Chapman & Hall/CRC Applied Environmental Statistics
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Taschenbuch. Condizione: Neu. Bringing Bayesian Models to Life | Mevin B. Hooten (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2021 | CRC Press | EAN 9781032092416 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2021
Serie: Chapman & Hall/CRC Applied Environmental Statistics, Libro 10 di 15. Libro 10 di 15 - Chapman & Hall/CRC Applied Environmental Statistics
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Paperback. Condizione: new. Paperback. Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the use…r to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models. Features:R code implementing algorithms to fit Bayesian models using real and simulated data examples.A comprehensive review of statistical models commonly used in ecological and environmental science.Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC.Derivations of the necessary components to construct statistical algorithms from scratch.Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites. This book presents details and algorithms for fully Bayesian computation, primarily for students and practitioners in the ecological and environmental sciences. It empowers the reader to extend and enhance statistical models for such data without software limitations. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Lingua: Inglese
Editore: Taylor & Francis Ltd, 2021
Serie: Chapman & Hall/CRC Applied Environmental Statistics, Libro 10 di 15. Libro 10 di 15 - Chapman & Hall/CRC Applied Environmental Statistics
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Lingua: Inglese
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Serie: Chapman & Hall/CRC Applied Environmental Statistics, Libro 10 di 15. Libro 10 di 15 - Chapman & Hall/CRC Applied Environmental Statistics
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Lingua: Inglese
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Lingua: Inglese
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical m…odels to computer algorithms. These algorithms allow the user to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models. Features:R code implementing algorithms to fit Bayesian models using real and simulated data examples.A comprehensive review of statistical models commonly used in ecological and environmental science.Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC.Derivations of the necessary components to construct statistical algorithms from scratch.Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites. 592 pp. Englisch.

Lingua: Inglese
Editore: CRC Press, 2021
Serie: Chapman & Hall/CRC Applied Environmental Statistics, Libro 10 di 15. Libro 10 di 15 - Chapman & Hall/CRC Applied Environmental Statistics
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Mevin B. Hooten is a Professor in the Departments of Fish, Wildlife, & Conservation Biology and Statistics at Colorado State University. He is also Assistant Unit Leader of the Colorado Cooperative Fish and Wildli…fe Research Unit (U.S. Geological Sur.

Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2021
Serie: Chapman & Hall/CRC Applied Environmental Statistics, Libro 10 di 15. Libro 10 di 15 - Chapman & Hall/CRC Applied Environmental Statistics
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Paperback. Condizione: new. Paperback. Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the use…r to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models. Features:R code implementing algorithms to fit Bayesian models using real and simulated data examples.A comprehensive review of statistical models commonly used in ecological and environmental science.Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC.Derivations of the necessary components to construct statistical algorithms from scratch.Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites. This book presents details and algorithms for fully Bayesian computation, primarily for students and practitioners in the ecological and environmental sciences. It empowers the reader to extend and enhance statistical models for such data without software limitations. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Lingua: Inglese
Editore: CRC Press, 2021
Serie: Chapman & Hall/CRC Applied Environmental Statistics, Libro 10 di 15. Libro 10 di 15 - Chapman & Hall/CRC Applied Environmental Statistics
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models… to computer algorithms. These algorithms allow the user to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models. Features:R code implementing algorithms to fit Bayesian models using real and simulated data examples.A comprehensive review of statistical models commonly used in ecological and environmental science.Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC.Derivations of the necessary components to construct statistical algorithms from scratch.Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites.

Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2021
Serie: Chapman & Hall/CRC Applied Environmental Statistics, Libro 10 di 15. Libro 10 di 15 - Chapman & Hall/CRC Applied Environmental Statistics
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Paperback. Condizione: new. Paperback. Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the use…r to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models. Features:R code implementing algorithms to fit Bayesian models using real and simulated data examples.A comprehensive review of statistical models commonly used in ecological and environmental science.Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC.Derivations of the necessary components to construct statistical algorithms from scratch.Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites. This book presents details and algorithms for fully Bayesian computation, primarily for students and practitioners in the ecological and environmental sciences. It empowers the reader to extend and enhance statistical models for such data without software limitations. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.