rmono {monomvn}R Documentation

Randomly Impose a Monotone Missingness Pattern

Description

Randomly impose a monotone missingness pattern by replacing the ends of each column of the input matrix by a random number of NAs

Usage

rmono(x, m = 7, ab = NULL)

Arguments

x data matrix
m minimum number of non-NA entries in each column
ab a two-vector of alpha (ab[1]) and beta (ab[2]) parameters to a Beta(alpha, beta) distribution describing the proportion of NA entries in each column. The default setting ab = NULL yields a uniform distribution

Details

The returned x always has one (randomly selected) complete column, and no column has fewer than m non-missing entries. Otherwise, the proportion of missing entries in each column can be uniform, or it can have a beta distribution with parameters alpha (ab[1]) and beta (ab[2])

Value

returns a matrix with the same dimensions as the input x

Author(s)

Robert B. Gramacy bobby@statslab.cam.ac.uk

References

http://www.statslab.cam.ac.uk/~bobby/monomvn.html

See Also

randmvn

Examples

out <- randmvn(10, 3)
rmono(out$x)

[Package monomvn version 1.6-1 Index]