rmsd.yai {yaImpute}R Documentation

Root Mean Square Difference between observed and imputed

Description

Computes the root mean square difference (RMSD) between observed and imputed values for each observation that has both. RMSD is computationally like RMSE, but they differ in interpretation. By default the RMSD values are scaled by the standard deviation of the respective variable.

Usage

rmsd.yai (object,vars=NULL,scale=FALSE,...)

Arguments

object an object created by yai or impute.yai
vars a list of variable names you want to include, if NULL all available variables are included
scale when TRUE, the values are scaled (see details)
... passed to called methods, very useful for passing arugment ancillaryData to function impute.yai

Details

By default, RMSD is computed using standard formula for its related statistic, RMSE. When scale=TRUE, RMSD is divided by the standard deviation of the observed data. The standard deviation is computed over the original list of reference observations and is therefore not influenced by the number of times a given reference is used for imputation.

Value

A data frame with the row names as vars and the column as rmsd. When scale=TRUE, the column name is rmsdS.

Author(s)

Nicholas L. Crookston ncrookston@fs.fed.us
Andrew O. Finley finleya@msu.edu

See Also

yai, impute.yai and http://www.jstatsoft.org/v23/i10.


[Package yaImpute version 1.0-8 Index]