generateSeedVectors {dqrng} R Documentation

## Generate seed as a integer vector

### Description

Generate seed as a integer vector

### Usage

generateSeedVectors(nseeds, nwords = 2L)


### Arguments

 nseeds Integer scalar, number of seeds to generate. nwords Integer scalar, number of words to generate per seed.

### Details

Each seed is encoded as an integer vector with the most significant bits at the start of the vector. Each integer vector is converted into an unsigned integer (in C++ or otherwise) by the following procedure:

2. Add the first value of the vector.

3. Left-shift the sum by 32.

4. Add the next value of the vector, and repeat.

The aim is to facilitate R-level generation of seeds with sufficient randomness to cover the entire state space of pseudo-random number generators that require more than the ~32 bits available in an int. It also preserves the integer nature of the seed, thus avoiding problems with casting double-precision numbers to integers.

It is possible for the seed vector to contain NA_integer_ values. This should not be cause for alarm, as R uses -INT_MAX to encode missing values in integer vectors.

### Value

A list of length n, where each element is an integer vector that contains nwords words (i.e., 32*nwords bits) of randomness.

Aaron Lun

### Examples

generateSeedVectors(10, 2)

generateSeedVectors(5, 4)



[Package dqrng version 0.3.0 Index]