R: Root Mean Square Difference between observed and imputed
rmsd.yai
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. The RMSD
values can be scaled to afford comparisons among variables.
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), if a named vector,
the values are scaled by the corresponding values.
...
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, or set of values is supplied, RMSD is divided by the
scaling factor. The scaling factor is the standard deviation of the
reference observations under the assumption that they are representative
of the population.
Value
A data frame with the row names as vars and the column as rmsd. When
scale=TRUE, the column name is rmsdS. The scaling factors used, if any,
are returned as an attribute.