Root Mean Square Difference between observed and imputed


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.





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 arugment ancillaryData to function impute.yai


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.


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.


Nicholas L. Crookston
Andrew O. Finley

See Also

yai, impute.yai and

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