Statistical modelling in R

Mathematics and Statistics

Research output: Book/Report/Proceedings › Book

Published

Standard

Statistical modelling in R. / Aitkin, Murray; Francis, Brian; Hinde, John et al.
Oxford: Oxford University Press, 2009. 568 p. (Oxford Statistical Science Series).

Research output: Book/Report/Proceedings › Book

Harvard

Aitkin, M, Francis, B, Hinde, J & Darnell, R 2009, Statistical modelling in R. Oxford Statistical Science Series, Oxford University Press, Oxford.

APA

Aitkin, M., Francis, B., Hinde, J., & Darnell, R. (2009). Statistical modelling in R. (Oxford Statistical Science Series). Oxford University Press.

Vancouver

Aitkin M, Francis B, Hinde J, Darnell R. Statistical modelling in R. Oxford: Oxford University Press, 2009. 568 p. (Oxford Statistical Science Series).

Author

Aitkin, Murray ; Francis, Brian ; Hinde, John et al. / Statistical modelling in R. Oxford : Oxford University Press, 2009. 568 p. (Oxford Statistical Science Series).

Bibtex

@book{38ee6122ce944a95ba294572214582b4,

title = "Statistical modelling in R",

abstract = "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 of Statistical Modelling. 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.",

author = "Murray Aitkin and Brian Francis and John Hinde and Ross Darnell",

year = "2009",

language = "English",

isbn = "9780199219131",

series = "Oxford Statistical Science Series",

publisher = "Oxford University Press",

}

RIS

TY - BOOK

T1 - Statistical modelling in R

AU - Aitkin, Murray

AU - Francis, Brian

AU - Hinde, John

AU - Darnell, Ross

PY - 2009

Y1 - 2009

N2 - 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 of Statistical Modelling. 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.

AB - 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 of Statistical Modelling. 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.

M3 - Book

SN - 9780199219131

SN - 0199219133

T3 - Oxford Statistical Science Series

BT - Statistical modelling in R

PB - Oxford University Press

CY - Oxford

ER -

Research