R2 {compositions} | R Documentation |

## 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)
## Default S3 method:
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 |

### 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`

.

### Value

The R2 measure of determination.

### Author(s)

K.Gerald v.d. Boogaart http://www.stat.boogaart.de

### See Also

### Examples

```
data(Orange)
R2(lm(circumference~age,data=Orange))
R2(lm(log(circumference)~log(age),data=Orange))
```

*compositions*version 2.0-8 Index]