R: Normalized Root Mean Squared Error

nrmse {missForest} | R Documentation

## Normalized Root Mean Squared Error

### Description

'nrmse' computes the normalized root mean squared error for a given complete data matrix, imputed data matrix and the data matrix containing missing values.

### Usage

    nrmse(ximp, xmis, xtrue)

### Arguments

`ximp` | imputed data matrix with variables in the columns and observations in the rows. Note there should not be any missing values.
`xmis` | data matrix with missing values.
`xtrue` | complete data matrix. Note there should not be any missing values.

### Value

see Title.

### Note

The NRMSE can only be computed for continuous data. For categorical or mixed-type data see `mixError`.

This function is internally used by `mixError`.

### Author(s)

Daniel J. Stekhoven, <stekhoven@stat.math.ethz.ch>

### References

Oba et al. (2003), 'A Bayesian missing value estimation method for gene expression profile data', Bioinformatics, 19(16), 2088-2096

### See Also

`mixError`

[Package missForest version 1.4 Index]