default_wf: K-means clustering with build-in missing data imputation

In ClustImpute: K-Means Clustering with Build-in Missing Data Imputation

Description

Default weight function. One minus the return value is multiplied with missing(=imputed) values. It starts with 1 and goes to 0 at n_end.

Usage

default_wf(n, n_end = 10)

Arguments

n	current step
n_end	steps until convergence of weight function to 0

Value

value between 0 and 1

Examples

x <- 0:20
plot(x,1-default_wf(x))

ClustImpute documentation built on May 31, 2021, 9:06 a.m.