Abstract
Linear models form the core of classical statistics, and S provides extensive facilities to fit and manipulate them. These work with a version of the Wilkinson-Rogers syntax (Wilkinson & Rogers, 1973) for specifying models which we discuss in the Section 6.2, and which is also used for generalized linear models, models for survival analysis and tree-based models in later chapters. The main function for fitting linear models is lm, which provides our first example of a style of S functions we shall see repeatedly in later chapters, producing a fitted model object which is then analysed by generic functions.
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© 1994 Springer Science+Business Media New York
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Venables, W.N., Ripley, B.D. (1994). Linear Statistical Models. In: Modern Applied Statistics with S-Plus. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-2819-1_6
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DOI: https://doi.org/10.1007/978-1-4899-2819-1_6
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4899-2821-4
Online ISBN: 978-1-4899-2819-1
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