Generalized Linear Models With Examples in R

Zusatztext

*This book eases students into GLMs and motivates the need for GLMs by starting with regression.* A practical working knowledge of good applied statistical practice is developed through the use of these real data sets and numerous case studies*. Each example in the text is cross-referenced with the relevant data set so that readers can load this data to follow the analysis in their own R session.

Autorenportrait

Peter K. Dunn is Associate Professor in the Faculty of Science, Health, Education and Engineering at the University of the Sunshine Coast. His work focuses on mathematical statistics, in particular generalized linear models. He has developed methods for accurate numerical evaluation of the densities of the Tweedie distributions, leading to a better understanding of these distributions. An engaging teacher, Dunn is the recipient of an Australian Office of Learning and Teaching citation. He has also won several conference paper prizes, including the EJ Pitman Prize at the Australian Statistics Conference.  He is a member of the Statistical Society of Australia Inc. and the Australian Mathematics Society.  Gordon K. Smyth is Head of the Bioinformatics Division at the Walter and Eliza Hall Institute of Medical Research and Honorary Professor of Mathematics & Statistics at The University of Melbourne. He has published research on generalized linear models and statistical computing for over 30 years and is the author of several popular R packages. In recent years, he has particularly promoted the use of generalized linear models to model data from genomic sequencing technologies.

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