Hefley Trevor (26 results)

Hardcover. Octavo, xv, 573 pages. In Good plus condition. Spine is black with white print. Boards in glossy illustrated paper. Slight shelf wear. Text block has penciled note on copyright page. Illustrated: b&w graphs, figures. NOTE: Shelved in Netdesk Column P. 1395114. FP New Rockville Stock.

Paperback. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Condition: New.

Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.

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Condition: New.

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Condition: New. In English.

Hardcover. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New.

Paperback. Condition: Brand New. 590 pages. 9.21x6.14x1.34 inches. In Stock.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New. In English.

Gebunden. Condition: New. Mevin B. Hooten is a Professor in the Departments of Fish, Wildlife, &amp Conservation Biology and Statistics at Colorado State University. He is also Assistant Unit Leader of the Colorado Cooperative Fish and Wildlife Research Unit (U.S. Geological Sur.

Hardcover. Condition: Brand New. 573 pages. 9.25x6.25x1.50 inches. In Stock.

Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Taschenbuch. Condition: 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 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. 592 pp. Englisch.…

Condition: 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, &amp Conservation Biology and Statistics at Colorado State University. He is also Assistant Unit Leader of the Colorado Cooperative Fish and Wildlife Research Unit (U.S. Geological Sur.…

Taschenbuch. Condition: 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.…