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- 000 03630cam a2200301 a 4500
- 008 111018s2012 flua b 001 0 eng
- 020 __ |a 9781439873656 (hardback) : |c CNY491.22
- 020 __ |a 1439873658 (hardback)
- 035 __ |a (OCoLC)ocn701015747
- 040 __ |a DLC |c DLC |d YDX |d BTCTA |d YDXCP |d BWX |d DLC
- 050 00 |a QA279 |b .H39 2012
- 082 00 |a 519.50285/5133 |2 23
- 100 1_ |a Hay-Jahans, Christopher.
- 245 13 |a An R companion to linear statistical models / |c Christopher Hay-Jahans.
- 260 __ |a Boca Raton, FL : |b CRC Press, |c c2012.
- 300 __ |a xvii, 354 p. : |b ill. ; |c 25 cm.
- 504 __ |a Includes bibliographical references and index.
- 520 __ |a "Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: Those who are familiar with the theory and applications of linear statistical models and wish to learn or enhance their skills in R; and those who are enrolled in an R-based course on regression and analysis of variance. For those who have never used R, the book begins with a self-contained introduction to R that lays the foundation for later chapters.This book includes extensive and carefully explained examples of how to write programs using the R programming language. These examples cover methods used for linear regression and designed experiments with up to two fixed-effects factors, including blocking variables and covariates. It also demonstrates applications of several pre-packaged functions for complex computational procedures. "-- |c Provided by publisher.
- 520 __ |a "Preface This work (referred to as Companion from here on) targets two primary audiences: Those who are familiar with the theory and applications of linear statistical models and wish to learn how to use R or supplement their abilities with R through unfamiliar ideas that might appear in this Companion; and those who are enrolled in a course on linear statistical models for which R is the computational platform to be used. About the Content and Scope While applications of several pre-packaged functions for complex computational procedures are demonstrated in this Companion, the focus is on programming with applications to methods used for linear regression and designed experiments with up to two fixed-effects factors, including blocking variables and covariates. The intent in compiling this Companion has been to provide as comprehensive a coverage of these topics as possible, subject to the constraint on the Companion's length. The reader should be aware that much of the programming code presented in this Companion is at a fairly basic level and, hence, is not necessarily very elegant in style. The purpose for this is mainly pedagogical; to match instructions provided in the code as closely as possible to computational steps that might appear in a variety of texts on the subject. Discussion on statistical theory is limited to only that which is necessary for computations; common "rules of thumb" used in interpreting graphs and computational output are provided. An effort has been made to direct the reader to resources in the literature where the scope of the Companion is exceeded, where a theoretical refresher might be useful, or where a deeper discussion may be desired. The bibliography lists a reasonable starting point for further references at a variety of levels"-- |c Provided by publisher.
- 650 _0 |a Linear models (Statistics)
- 650 _0 |a R (Computer program language)