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compositions (version 1.10-1)

R2: R square

Description

The R2 measure of determination for linear models

Usage

R2(object,...)
## S3 method for class 'lm':
R2(object,...,adjust=TRUE,ref=0)
## S3 method for class 'default':
R2(object,...,ref=0)

Arguments

object
a statistical model
...
further not yet used parameters
adjust
Logical, whether the estimate of R2 should be adjusted for the degrees of freedom of the model.
ref
A reference model for computation of a relative $R^2$.

Value

  • The R2 measure of determination.

Details

The $R^2$ measure of determination is defined as: $$R^2=1-\frac{var(residuals)}{var(data)}$$

and provides the portion of variance explained by the model. It is a number between 0 and 1, where 1 means the model perfectly explains the data and 0 means that the model has no better explanation of the data than a constant mean. In case of multivariate models metric variances are used. If a reference model is given by ref, the variance of the residuals of that models rather than the variance of the data is used. The value of such a relative $R^2$ estimates how much of the residual variance is explained. If adjust=TRUE the unbiased estiamators for the variances are used, to avoid the automatisme that a more parameters automatically lead to a higher $R^2$.

See Also

lm, mvar, AIC

Examples

Run this code
data(Orange)
R2(lm(circumference~age,data=Orange))
R2(lm(log(circumference)~log(age),data=Orange))

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