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Last data update: 2014.03.03

R: Randomly Impose a Monotone Missingness Pattern

rmono

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 rbgramacy@chicagobooth.edu

References

http://bobby.gramacy.com/r_packages/monomvn

Examples

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