missing.gen: Generating random missing values on a data matrix

In GenForImp: The Forward Imputation: A Sequential Distance-Based Approach for Imputing Missing Data

Description

The function generates a number of missing values (NA) completely at random on a data matrix. Totally missing rows (i.e., rows with all NA) are avoided.

Usage

missing.gen(mat, nummiss)

Arguments

mat	a matrix of numerical data.
nummiss	number of missing values.

Details

The function generates a number of missing values (NA) completely at random on a data matrix. Totally missing rows (i.e., rows with all NA) are avoided.

Value

The data matrix with missing values (NA).

Author(s)

Nadia Solaro, Alessandro Barbiero, Giancarlo Manzi, Pier Alda Ferrari

See Also

missing.gen0

Examples

sigma <- matrix(0.4, 4, 4)
diag(sigma) <- 1
x0 <- rmvnorm(n=100, mean=rep(0, 4), sigma=sigma)
x0 # complete matrix
x <- missing.gen(x0, 50)
x # matrix with 50 missing values

GenForImp documentation built on May 2, 2019, 2:15 p.m.