RandomNbinomArray-class {DelayedRandomArray} | R Documentation

## DelayedArray of random negative binomial values

### Description

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

### Usage

    RandomNbinomArraySeed(
      dim,
      prob = prob,
      size = size,
      mu = mu,
      chunkdim = NULL,
      sparse = FALSE
    )

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

    RandomNbinomArray(dim, prob, size, mu, chunkdim = NULL, sparse = FALSE)

### Arguments

`dim` | Integer vector of positive length, specifying the dimensions of the array.
`prob, size, mu` | Numeric vector used as the argument of the same name in `qnbinom`. Alternatively, a numeric array-like object with the same dimensions as `dim`. Exactly one of `prob` or `mu` should be supplied.
`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 RandomNbinomArraySeed object.

### Value

All constructors return an instance of a RandomNbinomArray object, containing random draws from a negative binomial distribution with the specified parameters.

### Author(s)

Aaron Lun

### See Also

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

### Examples

    X <- RandomNbinomArraySeed(c(1e5, 1e5), size=10, mu=20)
    Y <- DelayedArray(X)
    Y

    # Fiddling with the distribution parameters:
    X2 <- RandomNbinomArraySeed(c(1e5, 1e5), size=10, mu=runif(1e5), sparse=TRUE)
    Y2 <- DelayedArray(X2)
    Y2

    # Using another array as input:
    library(Matrix)
    lambda <- rsparsematrix(1e5, 1e5, density=0.00001)
    lambda <- abs(DelayedArray(lambda)) + 0.1
    X3 <- RandomNbinomArraySeed(c(1e5, 1e5), size=1, mu=lambda)
    Y3 <- DelayedArray(X3)
    Y3

[Package DelayedRandomArray version 1.2.0 Index]