RandomHyperArray-class {DelayedRandomArray} | R Documentation

## DelayedArray of random hypergeometric-distributed values

### Description

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

### Usage

    RandomHyperArraySeed(dim, m, n, k, chunkdim = NULL, sparse = FALSE)

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

    RandomHyperArray(dim, m, n, k, chunkdim = NULL, sparse = FALSE)

### Arguments

`dim` | Integer vector of positive length, specifying the dimensions of the array.
`m, n, k` | Numeric vector used as the argument of the same name in `qhyper`. 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 RandomHyperArraySeed object.

### Value

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

### Author(s)

Aaron Lun

### See Also

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

### Examples

    X <- RandomHyperArraySeed(c(1e5, 1e5), m=10, n=20, k=15)
    Y <- DelayedArray(X)
    Y

    # Fiddling with the distribution parameters:
    X2 <- RandomHyperArraySeed(c(1e5, 1e5), m=round(runif(1e5, 10, 20)),
        n=20, k=15, sparse=TRUE)
    Y2 <- DelayedArray(X2)
    Y2

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

[Package DelayedRandomArray version 1.2.0 Index]