measure_stekhoven_2012: Measure change between completed data sets as per Stekhoven...

In stephematician/miForang: Single or multiple imputation of missing data using random forests

Description

Measures a relationship between two supplied completed data sets, typically generated by two sequential iterations of the missForest procedure. Given by a Frobenius norm-based relative difference or the proportion of stationary values for continuous and categorical (included ordered) data respectively, as in Stekhoven and Buehlmann (2012).

Usage

measure_stekhoven_2012(X, Y, X_init, indicator)

Arguments

X	named list; imputed values of each variable (named) from one iteration within missForest procedure.
Y	list; imputed values of each variable (named) from the iteration within the missForest procedure succeeding that used to determine X.
X_init	data.frame; a data set including any of numeric, logical, integer, factor and ordered data types, to be used as the initial state of the missForest procedure.
indicator	named list; an indicator of the missing (=T) or not-missing (=F) status of the columns of X_init.

Details

Measures a relationship between two supplied completed data sets, typically generated by two sequential iterations of the missForest procedure. Intended to be used with the stop criterion that as soon as all values (see below) remain constant or decrease at once, then the missForest procedure is deemed to have converged. These are as per the original Stekhoven and Buehlmann (2012) paper.

The two measures are the;

• sum of the differences squared of all continuous data divided by the sum of the squares of the continuous data in the second supplied completed data set, and;

• proportion of stationary categorical data between the two supplied completed data sets (see stationary_rate).

The first item is referred to here as a Frobenius norm-based relative difference in the completed data.

Value

named numeric; two named values:

continuous

a Frobenius normi-based relative difference of the continuous data between the two completed data sets, and;

categorical

proportion of stationary values of categorical (including ordered) data between the two completed data sets (see stationary_rate).

References

Stekhoven, D.J. and Buehlmann, P., 2012. MissForest–non-parametric missing value imputation for mixed-type data. Bioinformatics, 28(1), pp. 112-118. doi.1.1093/bioinformatics/btr597

See Also

measure_correlation smirf stationary_rate

Examples

## Not run: 
# simply pass to smirf
smirf(iris, stop.measure=measure_stekhoven_2012)

## End(Not run)

stephematician/miForang documentation built on July 23, 2019, 5:11 p.m.