Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models (Chapman & Hall/CRC Texts in Statistical Science)
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Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models (Chapman & Hall/CRC Texts in Statistical Science)

by Julian J. Faraway

Programming Mathematics statistics
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Extending the Linear Model with R presents a focused study of generalized linear, mixed-effects, and nonparametric regression models. Written by Julian J. Faraway, this Chapman & Hall/CRC Texts in Statistical Science title connects advanced statistical modeling with the R programming environment.

About This Book

Extending the Linear Model with R examines statistical modeling beyond the traditional linear framework.

The book covers generalized linear models, mixed-effects models, and nonparametric regression models.

R is central to the presentation, connecting statistical methods with computational practice.

Published as part of the Chapman & Hall/CRC Texts in Statistical Science series, it provides a focused resource on advanced regression topics.

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I will be using this book for: