2nd ed. — Hoboken (NJ): John Wiley & Sons, 2020. — 363 p. — (Wiley Series in Probability and Statistics). — ISBN 1119392373.
Handbook and reference guide for students and practitioners of statistical regression-based analyses in R.Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting
complex regressions in the
R statistical programming language. The authors’ thorough treatment of “classical” regression analysis in the first edition is complemented here by their discussion of
more advanced topics including time-to-event survival data and longitudinal and clustered data. The book further pays particular attention to methods that have become
prominent in the last few decades as increasingly large data sets have made new techniques and applications possible.
These include:
Regularization methods.
Smoothing methods.
Tree-based methods.
In the new edition of the Handbook, the data analyst’s toolkit is
explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are
available via an author-maintained website. Of interest to undergraduate and graduate students taking courses in statistics and regression, the
Handbook of Regression Analysis will also be invaluable to practicing
data scientists and statisticians.
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