computeNRMSE: Normalized Root Mean Squared Imputatoin Error

In wNNSel: Weighted Nearest Neighbor Imputation of Missing Values using Selected Variables

Description

This function computes the nrmalized root mean squared imputation error for a given complete/true data matrix, imputed data matrix and the data matrix with missing values.

Usage

computeNRMSE(x.miss, x.impute, x.true)

Arguments

x.miss	a matrix, having missing values
x.impute	an imputed data matrix. Note that it should not contain any missing values.
x.true	complete/true data matrix. Note that it should not contain any missing values.

Value

value of MSIE

Examples

  set.seed(3)
  x.true = matrix(rnorm(100),10,10)
  ## create 10% missing values in x
  x.miss = artifNA(x.true, 0.10)
  ## impute using wNNSel method
  x.impute = wNNSel.impute(x.miss)
  computeNRMSE(x.miss, x.impute, x.true)

Example output

[1] "Computing distance matrix..."
[1] "Distance matrix complete"
[1] 1.176002

wNNSel documentation built on May 2, 2019, 2:49 p.m.