Mixed effects models and extensions in ecology with R

• Main Authors: Zuur, Alain F. (Author), Ieno, Elena N. (Author), Walker, Neil. (Author), Saveliev, Anatoly A. (Author), Smith, Graham M. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: New York, NY : Springer New York : Imprint: Springer, 2009.
• Subjects: Life sciences.; Ecology.; Statistics.; Environmental sciences.; Life Sciences.; Statistics for Life Sciences, Medicine, Health Sciences.; Math. Appl. in Environmental Science.; Environmental Monitoring/Analysis.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-0-387-87458-6

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 project...

Table of Contents:

• Revision of regression and additive models
• Regression and additive models with different variances
• Regression and additive models for time series or spatial data
• Mixed effects models
• Revision of GLM and GAM
• GLMM and GAMM for time series or spatial data
• Case study chapter showing regression or additive model
• Case study chapter showing the use of regression or additive models for time series data
• Case study chapter showing the use of regression or additive model for spatial data
• Case study chapter showing the use of a mixed effect model
• Case study chapter showing the use of GLMM and GAMM for time series
• Case study chapter showing the use of GLM or GAMM for spatial data.