Mixed effects models and extensions in ecology with R / Alain F. Zuur ... et al.

Object Details

Author

Zuur, Alain F

Contents

Limitations of linear regression applied on ecological data -- Things are not always linear : additive modeling -- Dealing with heterogeneity -- Mixed effects modeling for nested data -- Violation of independence. Part 1 -- Violation of independence. Part 2 -- Meet the exponential family -- GLM and GAM for count data -- GLM and GAM for absence-presence and proportional data -- Zero-truncated and zero-inflated models for count data -- Generalised estimation equations -- GLMM and GAMM -- Estimating trends for Antarctic birds in relation to climate change / A.F. Zuur ... [et al.] -- Large scale impacts of land-use change in a Scottish farming catchment / A.F. Zuur ... [et al.] -- Negative binomial GAM and GAMM to analyse amphibian roadkills / A.F. Zuur ... [et al.] -- Additive mixed modelling applied on deep-sea pelagic bioluminescent organisms / A.F. Zuur ... [et al.] -- Additive mixed modelling applied on phytoplankton time series data / A.F. Zuur ... [et al.] -- Mixed effects modelling applied on American foulbrood affecting honey bees larvae / A.F. Zuur ... [et al.] -- Three-way nested data for age determination techniques applied to cetaceans / E.N. Ieno ... [et al.] -- GLMM applied on the spatial distribution of koalas in a fragmented landscape / J.R. Rhodes ... [et al.] -- A comparison of GLM, GEE, and GLMM applied to badger activity data / N.J. Walker ... [et al.] -- Incorporating temporal correlation in seal abundance data with MCMC / A.A. Saveliev ... [et al.] -- Required pre-knowledge : a linear regression and additive modelling example

Summary

"In this book the authors provide an expanded introduction to using regression and its extensions in analysing ecological data. 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 the reader's own data."--NHBS Environment Bookstore.

2009

Type

Books

Physical description

xxii, 574 p. : ill ; 25 cm

Smithsonian Libraries

Topic

Ecology--Statistical methods

R (Computer program language)

Record ID

siris_sil_949507

Metadata Usage (text)

CC0