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Hierarchical Modeling and Inference in Ecology - J. Andrew Royle
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Hierarchical Modeling and Inference in Ecology - neues Buch

ISBN: 9780080559254

ID: 9780080559254

The Analysis of Data from Populations, Metapopulations and Communities A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including \* occurrence or occupancy models for estimating species distribution\* abundance models based on many sampling protocols, including distance sampling\* capture-recapture models with individual effects\* spatial capture-recapture models based on camera trapping and related methods\* population and metapopulation dynamic models\* models of biodiversity, community structure and dynamics\* Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants)\* Development of classical, likelihood-based procedures for inference, as well asBayesian methods of analysis\* Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS\* Computing support in technical appendices in an online companion web site Hierarchical Modeling and Inference in Ecology: A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including \* occurrence or occupancy models for estimating species distribution\* abundance models based on many sampling protocols, including distance sampling\* capture-recapture models with individual effects\* spatial capture-recapture models based on camera trapping and related methods\* population and metapopulation dynamic models\* models of biodiversity, community structure and dynamics\* Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants)\* Development of classical, likelihood-based procedures for inference, as well asBayesian methods of analysis\* Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS\* Computing support in technical appendices in an online companion web site, Elsevier Science

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Hierarchical Modeling and Inference in Ecology, The Analysis of Data from Populations, Metapopulations and Communities - J. Andrew Royle, Robert M. Dorazio
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J. Andrew Royle, Robert M. Dorazio:
Hierarchical Modeling and Inference in Ecology, The Analysis of Data from Populations, Metapopulations and Communities - neues Buch

2008, ISBN: 9780080559254

ID: 1001004007444588

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models ..., A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, meta population, community, and meta community systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including: occurrence or occupancy models for estimating species distribution; abundance models based on many sampling protocols, including distance sampling; capture-recapture models with individual effects; spatial capture-recapture models based on camera trapping and related methods; population and meta population dynamic models; models of biodiversity, community structure and dynamics; wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants); development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis; detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS; and, computing support in technical appendices in an online companion web site. Productinformatie: Taal: Engels; Vertaald uit het: Engels; Formaat: ePub met kopieerbeveiliging (DRM) van Adobe; Bestandsgrootte: 10.63 MB; Kopieerrechten: Het kopiëren van (delen van) de pagina's is niet toegestaan ; Printrechten: Het printen van de pagina's is niet toegestaan; Voorleesfunctie: De voorleesfunctie is uitgeschakeld; Geschikt voor: Alle e-readers te koop bij bol.com (of compatible met Adobe DRM). Telefoons/tablets met Google Android (1.6 of hoger) voorzien van bol.com boekenbol app. PC en Mac met Adobe reader software; ISBN10: 0080559255; ISBN13: 9780080559254; , Engels | Ebook | 2008, School en studie, Exacte wetenschappen, Ecologie, School en studie, Exacte wetenschappen, Meer exacte wetenschappen, Academic Press

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Hierarchical Modeling and Inference in Ecology - Robert M. Dorazio#J. Andrew Royle
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Hierarchical Modeling and Inference in Ecology - neues Buch

2008, ISBN: 9780080559254

ID: 198020984

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics * Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) * Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis * Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS * Computing support in technical appendices in an online companion web site The Analysis of Data from Populations, Metapopulations and Communities eBooks > Fremdsprachige eBooks > Englische eBooks > Sach- & Fachthemen > Mathematik ePUB 15.10.2008 eBook, Elsevier Science, .200

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Hierarchical Modeling and Inference in Ecology - J. Andrew Royle
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
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J. Andrew Royle:
Hierarchical Modeling and Inference in Ecology - neues Buch

ISBN: 9780080559254

ID: 9780080559254

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures.The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution* abundance models based on many sampling protocols, including distance sampling* capture-recapture models with individual effects* spatial capture-recapture models based on camera trapping and related methods* population and metapopulation dynamic models* models of biodiversity, community structure and dynamics* Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants)* Development of classical, likelihood-based procedures for inference, as well asBayesian methods of analysis* Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS* Computing support in technical appendices in an online companion web site 9780123740977,9780080559254,0123740975,0080559255 Other pricing structure might be available at vitalsource.com., Elsevier S & T

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Hierarchical Modeling and Inference in Ecology - J. Andrew Royle;  Robert M. Dorazio
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2008, ISBN: 9780080559254

ID: 21794213

The Analysis of Data from Populations, Metapopulations and Communities, [ED: 1], Auflage, eBook Download (EPUB,PDF), eBooks, [PU: Academic Press]

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Details zum Buch
Hierarchical Modeling and Inference in Ecology
Autor:

Robert M. Dorazio;Royle, J. Andrew

Titel:

Hierarchical Modeling and Inference in Ecology

ISBN-Nummer:

Detailangaben zum Buch - Hierarchical Modeling and Inference in Ecology


EAN (ISBN-13): 9780080559254
Erscheinungsjahr: 2008
Herausgeber: Academic Press

Buch in der Datenbank seit 28.02.2007 23:38:33
Buch zuletzt gefunden am 23.05.2017 09:39:26
ISBN/EAN: 9780080559254

ISBN - alternative Schreibweisen:
978-0-08-055925-4


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