Statistical Modelling in R

Statistical Modelling in R

by Murray Aitkin, Brian Francis, John Hinde, Ross Darnell
     
 

R is now the most widely used statistical package/language in university statistics departments and many research organizations. Its great advantages are that for many years, it has been the leading statistical package/language and that it can be freely downloaded from the R website. This text provides a comprehensive treatment of the theory of statistical

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Overview

R is now the most widely used statistical package/language in university statistics departments and many research organizations. Its great advantages are that for many years, it has been the leading statistical package/language and that it can be freely downloaded from the R website. This text provides a comprehensive treatment of the theory of statistical modelling in R with an emphasis on applications to practical problems and an expanded discussion of statistical theory. A wide range of case studies is provided, using the normal, binomial, Poisson, multinomial, gamma, exponential and Weibull distributions, making this book ideal for graduates and research students in applied statistics and a wide range of qualitative disciplines.

Product Details

ISBN-13:
9780199219148
Publisher:
Oxford University Press
Publication date:
04/29/2009
Pages:
568
Product dimensions:
6.40(w) x 9.30(h) x 1.40(d)

Table of Contents

1 Introducing R 1

2 Statistical modelling and inference 28

3 Regression and analysis of variance 97

4 Binary response data 195

5 Multinomial and Poisson response data 269

6 Survival data 347

7 Finite mixture models 433

8 Random effect models 461

9 Variance component models 508

Bibliography 554

R function and constant index 567

Dataset index 570

Subject index 571

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