RandomWilcoxArray-class {DelayedRandomArray} | R Documentation

## DelayedArray of random Wilcoxon-distributed values

### Description

A DelayedArray subclass that performs on-the-fly sampling of Wilcoxon-distributed values.

### Usage

    RandomWilcoxArraySeed(dim, m, n, chunkdim = NULL, sparse = FALSE)

    ## S4 method for signature 'RandomWilcoxArraySeed'
    DelayedArray(seed)

    RandomWilcoxArray(dim, m, n, chunkdim = NULL)

### Arguments

`dim` | Integer vector of positive length, specifying the dimensions of the array.
`m, n` | Numeric vector used as the argument of the same name in `qwilcox`. Alternatively, a numeric array-like object with the same dimensions as `dim`.
`chunkdim` | Integer vector of length equal to `dim`, containing the dimensions of each chunk.
`sparse` | Logical scalar indicating whether the sampled array should be treated as sparse.
`seed` | A RandomWilcoxArraySeed object.

### Value

All constructors return an instance of a RandomWilcoxArray object, containing random draws from a Wilcox distribution with the specified parameters.

### Author(s)

Aaron Lun

### See Also

The RandomArraySeed class, for details on chunking and the distributional parameters.

### Examples

    X <- RandomWilcoxArraySeed(c(1e5, 1e5), m=10, n=20)
    Y <- DelayedArray(X)
    Y

    # Fiddling with the distribution parameters:
    X2 <- RandomWilcoxArraySeed(c(1e5, 1e5), m=round(runif(1e5, 10, 20)), n=20)
    Y2 <- DelayedArray(X2)
    Y2

    # Using another array as input:
    library(Matrix)
    m <- round(RandomUnifArray(c(1e5, 1e5), 10, 20))
    X3 <- RandomWilcoxArraySeed(c(1e5, 1e5), m=m, n=50)
    Y3 <- DelayedArray(X3)
    Y3

[Package DelayedRandomArray version 1.0.0 Index]