Statistical Modelling in R
Murray Aitkin (Professorial Fellow, Department of Mathematics and Statistics, University of Melbourne),Brian Francis (Department of Mathematics and Statistics, Lancaster University),John Hinde (Professor of Statistics, School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway),Ross Darnell (Senior Applied Statistician, CSIRO Mathematical and Information Sciences, Australia)
Statistical Modelling in R
Murray Aitkin (Professorial Fellow, Department of Mathematics and Statistics, University of Melbourne),Brian Francis (Department of Mathematics and Statistics, Lancaster University),John Hinde (Professor of Statistics, School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway),Ross Darnell (Senior Applied Statistician, CSIRO Mathematical and Information Sciences, Australia)
R is now the most widely used statistical package/language in university statistics departments and many research organisations. Its great advantages are that for many years it has been the leading-edge statistical package/language and that it can be freely downloaded from the R web site. Its cooperative development and open code also attracts many contributors meaning that the modelling and data analysis possibilities in R are much richer than in GLIM4, and so the R edition can be substantially more comprehensive than the GLIM4 edition.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 quantitative disciplines.
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