By William N. Venables, David M. Smith, R Development Core Team

ISBN-10: 3900051127

ISBN-13: 9783900051129

**Read Online or Download An Introduction to R: Notes on R: A Programming Environment for Data Analysis and Graphics PDF**

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**Additional resources for An Introduction to R: Notes on R: A Programming Environment for Data Analysis and Graphics**

**Sample text**

Y ~ (A + B + C)^2 y ~ A*B*C - A:B:C Three factor experiment but with a model containing main effects and two factor interactions only. Both formulae specify the same model. y~A*x y ~ A/x y ~ A/(1 + x) - 1 Separate simple linear regression models of y on x within the levels of A, with different codings. The last form produces explicit estimates of as many different intercepts and slopes as there are levels in A. y ~ A*B + Error(C) An experiment with two treatment factors, A and B, and error strata determined by factor C.

For example a split plot experiment, with whole plots (and hence also subplots), determined by factor C. The operator ~ is used to define a model formula in R. The form, for an ordinary linear model, is response ~ op_1 term_1 op_2 term_2 op_3 term_3 ... where response is a vector or matrix, (or expression evaluating to a vector or matrix) defining the response variable(s). op i is an operator, either + or -, implying the inclusion or exclusion of a term in the model, (the first is optional). term i is either • a vector or matrix expression, or 1, • a factor, or • a formula expression consisting of factors, vectors or matrices connected by formula operators.

Frame, graph=TRUE, limit=20) { ... } it could be called as > ans <- fun1(d, df) which is now equivalent to the three cases above, or as > ans <- fun1(d, df, limit=10) which changes one of the defaults. It is important to note that defaults may be arbitrary expressions, even involving other arguments to the same function; they are not restricted to be constants as in our simple example here. ’ argument Another frequent requirement is to allow one function to pass on argument settings to another.

### An Introduction to R: Notes on R: A Programming Environment for Data Analysis and Graphics by William N. Venables, David M. Smith, R Development Core Team

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