Overview

Usage:

import betterr.random;

This module exposes all of the random number generation function in base R to a D program.

Source Code and Examples

• Source Code
• Examples

Structs

Sample

struct Sample {
    Vector x;
    long size;
    bool replace = false;
    Vector prob;
}

Data

• x: Vector holding the data to be sampled.
• size: Number of elements to sample from x.
• replace: True if sampling from x is done with replacement.
• prob: A vector specifying the probabilities of drawing each of the elements of x.

Methods

• draw(): Return a vector holding the sample drawn based on the configuration you have specified.

See also: R documentation

Functions

rnorm

Vector rnorm(long n, double mean=0, double sd=1)

• n: Number of draws
• mean
• sd: Standard deviation

See also: rnorm

runif

Vector runif(long n, double min=0, double max=1)

• n: Number of draws
• min
• max

See also: runif

rgamma

Vector rgamma(long n, double shape, double rate=double.nan, double scale=1.0)

R has named optional parameters. D does not. Set rate to double.nan to leave it unspecified.

• n: Number of draws
• shape
• rate
• scale

See also: rgamma

rbeta

Vector rbeta(long n, double shape1, double shape2, double ncp=0.0)

• n: Number of draws
• shape1
• shape2
• ncp: Non-centrality parameter

See also: rbeta

rbinom

Vector rbinom(long n, long size, double prob)

• n: Number of draws
• size: Number of trials
• prob: Probability of success on each trial

See also: rbinom

rcauchy

Vector rcauchy(long n, double location=0, double scale=1)

• n: Number of draws
• location
• scale

See also: rcauchy

rchisq

Vector rchisq(long n, double df, double ncp)

• n: Number of draws
• df: Degrees of freedom (>= 0)
• ncp: Non-centrality parameter (>= 0)

See also: rchisq

rexp

Vector rexp(long n, double rate=1.0)

• n: Number of draws
• rate: Mean is 1/rate

See also: rexp

rf

Vector rf(long n, long df1, long df2, double ncp)
Vector rf(long n, long df1, long df2)

• n: Number of draws
• df1: First degrees of freedom parameter
• df2: Second degrees of freedom parameter
• ncp: Non-centrality parameter

See also: rf

rgeom

Vector rgeom(T)(long n, T prob)

• n: Number of draws
• prob: A Vector of probabilities or anything that converts to a Vector, including a double[].

See also: rgeom

rhyper

Vector rhyper(long nn, long m, long n, long k)
Vector rhyper(Vector nn, long m, long n, long k)
Vector rhyper(long[] nn, long m, long n, long k)

• nn: Number of draws (observations). If it is Vector or long[], then the number of draws is the number of elements of nn. This is consistent with the behavior of the underlying R function.
• m: Number of white balls
• n: Number of black balls
• k: Number of balls that are drawn from the urn to generate each observation

See also: rhyper

rlnorm

Vector rlnorm(long n, double meanlog=0, double sdlog=1)

• n: Number of draws
• meanlog: Mean of the distribution on the logscale
• sdlog: Standard deviation of the distribution on the logscale

See also: rlnorm

rmultinom

Matrix rmultinom(T)(long n, long size, T prob)

• n: Number of random vectors to draw
• size: Total number of elements drawn
• prob: Vector of probabilities of each of the elements that are drawn. The number of elements in each of the n vectors is size/prob.rows. prob can be a Vector, or anything that converts to a Vector.

See also: rmultinom

rnbinom

Vector rnbinom(long n, double size, double prob, double mu)
Vector rnbinom(Vector n, double size, double prob, double mu)
Vector rnbinom(T)(T[] n, double size, double prob, double mu)
Vector rnbinom(long n, double size, double prob)
Vector rnbinom(Vector n, double size, double prob)
Vector rnbinom(T)(T[] n, double size, double prob)

• n: Number of draws
• size: Target for number of successful trials
• prob: Probability of success in each trial
• mu: Alternative to specifying prob

If you want to specify mu rather than prob, set prob to double.nan. If n is a Vector or converts to a Vector, then the number of draws is n.rows.

See also: rnbinom

rpois

Vector rpois(double n, double lambda)

• n: Number of draws
• lambda: Mean

See also: rpois

rt

Vector rt(long n, double df, double ncp)
Vector rt(long n, double df)
Vector rt(Vector n, double df, double ncp)
Vector rt(Vector n, double df)
Vector rt(T)(T[] n, double df, double ncp)
Vector rt(T)(T[] n, double df)

• n: Number of draws. If n is a Vector or converts to a Vector, the number of draws is n.rows.
• df: Degrees of freedom
• ncp: Non-centrality parameter

See also: rt

rweibull

Vector rweibull(long n, double shape, double scale=1.0)

• n: Number of draws
• shape
• scale

See also: rweibull

Index    Repo