# getWithin

From DiscriMiner v0.1-29
by Gaston Sanchez

##### Within-class Covariance Matrix

Calculates the estimated within-class covariance matrix

##### Usage

`getWithin(variables, group)`

##### Arguments

- variables
- matrix or data frame with explanatory variables (No missing values are allowed)
- group
- vector or factor with group memberships (No missing values are allowed)

##### Details

The obtained matrix is the estimated within-class
covariance matrix (i.e. within-class covariance matrix
divided by its degrees of freedom `n-k`

, where
`n`

is the number of observations and `k`

is
the number of groups)

##### See Also

##### Examples

```
## Not run:
# # load iris dataset
# data(iris)
#
# # estimated within-class covariance matrix (dividing by n-k)
# getWithin(iris[,1:4], iris[,5])
#
# # compared to the within-class covariance matrix (dividing by n-1)
# withinCov(iris[,1:4], iris[,5])
# ## End(Not run)
```

*Documentation reproduced from package DiscriMiner, version 0.1-29, License: GPL-3*

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