reweight.data: Reweight Variables

In HotDeckImputation: Hot Deck Imputation Methods for Missing Data

Description

Reweighting function to preprocess a data matrix prior to Minkovski distance calculation.

Usage

reweight.data(DATA = NULL, weights = NULL, minkovski_factor = 1)

Arguments

DATA	Data that should be reweighted.
weights	Numeric vector with length equal to the number of variables in DATA.
minkovski_factor	The desired Minkovski parameter that will be used for calculating the distances.

Value

Returns a data matrix with the same dimensions as DATA.

Author(s)

Dieter William Joenssen [e-mail]

See Also

impute.NN_HD

Examples

#Set the random seed to an arbitrary number
set.seed(421)

#Generate matrix of random integers
Y<-matrix(sample(0:9,replace=TRUE,size=6*3),nrow=6)

#choose variable variances
Weights<-1/apply(X=Y,MARGIN=2,FUN=var)

#reweight data for faster Euclidean distance calculation
reweight.data(DATA = Y, weights = Weights, minkovski_factor = 2)

HotDeckImputation documentation built on May 2, 2019, 6:41 a.m.