nrmse: Normalized Root Mean Squared Error

In missForest: Nonparametric Missing Value Imputation using Random Forest

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, <[e-mail]>

References

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

See Also

mixError

missForest documentation built on April 14, 2022, 5:05 p.m.