R2 | R Documentation |
The R2 measure of determination for linear models
R2(object,...)
## S3 method for class 'lm'
R2(object,...,adjust=TRUE,ref=0)
## Default S3 method:
R2(object,...,ref=0)
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 |
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
.
The R2 measure of determination.
K.Gerald v.d. Boogaart http://www.stat.boogaart.de
lm
, mvar
, AIC
data(Orange)
R2(lm(circumference~age,data=Orange))
R2(lm(log(circumference)~log(age),data=Orange))
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