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Springer New York

Mixed Effects Models and Extensions in Ecology with R

Mixed Effects Models and Extensions in Ecology with R

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Building on the successful Analysing Ecological Data (2007) by Zuur, Ieno and Smith, the authors now provide an expanded introduction to using regression and its extensions in analysing ecological data. As with the earlier book, real data sets from postgraduate ecological studies or research projects are used throughout. The first part of the book is a largely non-mathematical introduction to linear mixed effects modelling, GLM and GAM, zero inflated models, GEE, GLMM and GAMM. The second part provides ten case studies that range from koalas to deep sea research. These chapters provide an invaluable insight into analysing complex ecological datasets, including comparisons of different approaches to the same problem. By matching ecological questions and data structure to a case study, these chapters provide an excellent starting point to analysing your own data. Data and R code from all chapters are available from www.highstat.com.

Author: Alain Zuur,Elena N. Ieno,Neil Walker,Anatoly A. Saveliev,Graham M. Smith

Publisher: Springer New York
Publish Date: 2011-04-06
Edition: Softcover reprint of hardcover 1st ed. 2009
ISBN: 1441927646
ISBN 13: 9781441927644
Dimension: Length: 6.1 inches, Width: 1.36 inches, Height: 9.25 inches
Weight: Weight: 2.00179733896 pounds
Binding: Paperback
Pages: 574

Building on the successful Analysing Ecological Data (2007) by Zuur, Ieno and Smith, the authors now provide an expanded introduction to using regression and its extensions in analysing ecological data. As with the earlier book, real data sets from postgraduate ecological studies or research projects are used throughout. The first part of the book is a largely non-mathematical introduction to linear mixed effects modelling, GLM and GAM, zero inflated models, GEE, GLMM and GAMM. The second part provides ten case studies that range from koalas to deep sea research. These chapters provide an invaluable insight into analysing complex ecological datasets, including comparisons of different approaches to the same problem. By matching ecological questions and data structure to a case study, these chapters provide an excellent starting point to analysing your own data. Data and R code from all chapters are available from www.highstat.com.

Author: Alain Zuur,Elena N. Ieno,Neil Walker,Anatoly A. Saveliev,Graham M. Smith

Publisher: Springer New York
Publish Date: 2011-04-06
Edition: Softcover reprint of hardcover 1st ed. 2009
ISBN: 1441927646
ISBN 13: 9781441927644
Dimension: Length: 6.1 inches, Width: 1.36 inches, Height: 9.25 inches
Weight: Weight: 2.00179733896 pounds
Binding: Paperback
Pages: 574