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 `NA`s

### 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 1.8 Index]