nrmse

imputed data matrix with variables in the columns and observations in
 the rows. Note there should not be any missing values.

ximp

xmis

complete data matrix. Note there should not be any missing values.

xtrue

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

 error 

The function 'missForest' in this package is used to
impute missing values particularly in the case of mixed-type
data. It uses a random forest trained on the observed values of
a data matrix to predict the missing values. It can be used to
impute continuous and/or categorical data including complex
interactions and non-linear relations. It yields an out-of-bag
(OOB) imputation error estimate without the need of a test set
or elaborate cross-validation. It can be run in parallel to
save computation time.

nrmse: Normalized Root Mean Squared Error

Description

Usage

Arguments

Value

References

See Also