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Hierarchical Modelling for the Environmental Sciences : Statistical Methods and Applications

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Title: Hierarchical Modelling for the Environmental Sciences : Statistical Methods and Applications
Description: New Statistical tools are changing the wau in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide constant framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirment for a clear exposition of the methodology through to application for a range of environmental challenges.
Authors: James S. Clark, Alan E. Gelfand
Resource Type: eBook.
Subjects: Mathematical statistics--Data processing, Environmental sciences--Statistical methods, Bayesian statistical decision theory, Multilevel models (Statistics)
Categories: SCIENCE / Life Sciences / Ecology, NATURE / Ecology, NATURE / Ecosystems & Habitats / Wilderness, SCIENCE / Environmental Science
Database: eBook Collection (EBSCOhost)
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Text:
  Availability: 0
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DbLabel: eBook Collection (EBSCOhost)
An: 192123
RelevancyScore: 1005
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1004.98577880859
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  Data: Hierarchical Modelling for the Environmental Sciences : Statistical Methods and Applications
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  Data: New Statistical tools are changing the wau in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide constant framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirment for a clear exposition of the methodology through to application for a range of environmental challenges.
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  Data: <searchLink fieldCode="AR" term="%22James+S%2E+Clark%22">James S. Clark</searchLink><br /><searchLink fieldCode="AR" term="%22Alan+E%2E+Gelfand%22">Alan E. Gelfand</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Mathematical+statistics--Data+processing%22">Mathematical statistics--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Environmental+sciences--Statistical+methods%22">Environmental sciences--Statistical methods</searchLink><br /><searchLink fieldCode="DE" term="%22Bayesian+statistical+decision+theory%22">Bayesian statistical decision theory</searchLink><br /><searchLink fieldCode="DE" term="%22Multilevel+models+%28Statistics%29%22">Multilevel models (Statistics)</searchLink>
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RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 577.01519542
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Mathematical statistics--Data processing
        Type: general
      – SubjectFull: Environmental sciences--Statistical methods
        Type: general
      – SubjectFull: Bayesian statistical decision theory
        Type: general
      – SubjectFull: Multilevel models (Statistics)
        Type: general
    Titles:
      – TitleFull: Hierarchical Modelling for the Environmental Sciences : Statistical Methods and Applications
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: James S. Clark
      – PersonEntity:
          Name:
            NameFull: Alan E. Gelfand
      – PersonEntity:
          Name:
            NameFull: James S. Clark
      – PersonEntity:
          Name:
            NameFull: Alan E. Gelfand
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2006
            – D: 04
              M: 02
              Type: profile
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9780198569664
            – Type: isbn-print
              Value: 9780198569671
            – Type: isbn-electronic
              Value: 9780191513848
          Titles:
            – TitleFull: Hierarchical Modelling for the Environmental Sciences : Statistical Methods and Applications
              Type: main
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