Introduction to WinBUGS for ecologists : a Bayesian approach to regression, ANOVA, mixed models and related analyses / Marc Kery.
Material type: TextPublication details: Amsterdam ; Boston : Elsevier, 2010.Edition: 1st edDescription: xviii, 302 p. : ill. (some col.) ; 23 cmISBN:- 9780123786050
- 0123786053
- 577.015118 22 KEI
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Books | Central Library, SUST General Stacks | 577.015118 KEI (Browse shelf(Opens below)) | 1 | Available | 0072874 | |
Books | Central Library, SUST General Stacks | 577.015118 KEI (Browse shelf(Opens below)) | 2 | Available | 0072875 | |
Books | Seminar Library, Deprment of Forestry & Environmental Science General Stacks | 577.015118 KEI (Browse shelf(Opens below)) | 3 | Available | 0074340 |
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577.015118 GRI Individual-based modeling and ecology / | 577.015118 GRI Individual-based modeling and ecology / | 577.015118 KEI Introduction to WinBUGS for ecologists : | 577.015118 KEI Introduction to WinBUGS for ecologists : | 577.015118 KEI Introduction to WinBUGS for ecologists : | 577.015118 PAM Mathematical ecology of populations and ecosystems / | 577.015118 SME Environmental modelling an introduction / |
Includes bibliographical references and index.
Introduction -- Introduction to Bayesian analysis of a statistical model -- WinBUGS -- A first session in WinBUGS : the "model of the mean" -- Running WinBUGS from R via R2WinBUGS -- Key components of (generalized) linear models : statistical distributions and the linear predictor -- t-Test : equal and unequal variances -- Normal linear regression -- Normal one-way ANOVA -- Normal two-way ANOVA -- General linear model (ANCOVA) -- Linear mixed-effects model -- Introduction to the generalized linear model : Poisson "t-test" -- Overdispersion, zero-inflation, and offsets in the GLM -- Poisson ANCOVA -- Poisson mixed-effects model (Poisson GLMM) -- Binomial "t-Test" -- Binomial analysis of covariance -- Binomial mixed-effects model (binomial GLMM) -- Nonstandard GLMMs 1 : site-occupancy species distribution model -- Nonstandard GLMMs 2 : binomial mixture model to model abundance -- Conclusions.
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