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.
rmsd.yai (object,vars=NULL,scale=FALSE,...)
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.
an object created by yai
or impute.yai
a list of variable names you want to include, if NULL all available variables are included
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 argument
ancillaryData
to function impute.yai
Nicholas L. Crookston ncrookston.fs@gmail.com
Andrew O. Finley finleya@msu.edu
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.
yai
, impute.yai
and tools:::Rd_expr_doi("https://doi.org/10.18637/jss.v023.i10").