A Beginner's Guide to GAMM with R is the third in Highland Statistics' Beginner's Guide series, following the well-received A Beginner's Guide to Generalized Additive Models with R and A Beginner's Guide to GLM and GLMM with R. In this book we take the reader on an exciting voyage into the world of generalised additive mixed effects models (GAMM). Keywords are GAM, mgcv, gamm4, random effects, Poisson and negative binomial GAMM, gamma GAMM, binomial GAMM, NB-P models, GAMMs with generalised extreme value distributions, overdispersion, underdispersion, two-dimensional smoothers, zero-inflated GAMMs, spatial correlation, INLA, Markov chain Monte Carlo techniques, JAGS, and two-way nested GAMMs. The book includes three chapters on the analysis of zero-inflated data. Throughout the book frequentist approaches (gam, gamm, gamm4, lme4) are compared with Bayesian techniques (MCMC in JAGS and INLA). Datasets on squid, polar bears, coral reefs, ruddy turnstones, parasites in anchovy, Common Guillemots, harbour porpoises, forestry, brood parasitism, maximum cod length, and Common Scoters are used in case studies. The R code to construct, fit, interpret, and comparatively evaluate models is provided at every stage (either in the book or on the website for the book).
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Alain F Zuur is senior statistician and director of Highland Statistics Ltd., a statistics consultancy based in the UK. He is the author of seven books on the analysis of ecological data. He has extensive experience teaching statistical methods to ecologists and environmental scientists in academic and nonacademic courses worldwide. Anatoly A Saveliev is a professor at the Institute of Ecology and Geography at Kazan Federal State University, Russian Federation, where he teaches GIS and statistics. He also provides consultancy in statistics, GIS and remote sensing, and spatial modelling, and software development in these areas. Elena N Ieno is senior marine biologist at Highland Statistics Ltd. She teaches data analysis to ecologists and has shown the ability to challenge the gap between both disciplines. She is co-author of six books on analysis of ecological data.Review:
This book is the foremost text on generalised additive mixed models. Presented from both the frequentist and Bayesian perspective using real ecological data, the theory is clearly explained, and full working code in R is provided so that an analyst can easily employ these methods into their own research. Professor Joseph M Hilbe. Arizona State University. Jet Propulsion Laboratory, Caltech
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