# rDiscrete: Generate a Random Data from Discrete Probability Function In rTableICC: Random Generation of Contingency Tables

## Description

Generates random data from a given empirical probability function. It also returns cumulative distribution function corresponding to the entered probability function.

## Usage

 `1` ```rDiscrete(n = 1, pf) ```

## Arguments

 `n` number of observations. `pf` empirical probability function.

## Details

`pf` is an array of any dimensionality with all elements sum up to one. If its dimension is greater than one, it is transformed to a row vector column-by-column.

## Value

A list including

 `rdiscrete` an nx1 vector that gives generated random data. `cdf` a vector including cumulative distribution function.

## Author(s)

Haydar Demirhan

Maintainer: Haydar Demirhan <[email protected]>

## References

Kroese D.P., Taimre T., Botev Z.I. (2011) Handbook of Monte Carlo Methods, Wiley, New York.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```p = c(0.23,0.11,0.05,0.03,0.31,0.03,0.22,0.02) rDiscrete(n=2,pf=p) # pf would be entered as a matrix: p = matrix(c(0.23,0.11,0.05,0.03,0.31,0.03,0.22,0.02), nrow=2, ncol=4, byrow = TRUE) rDiscrete(n=2,pf=p) p = matrix(c(0.23,0.11,0.05,0.03,0.31,0.03,0.22,0.02), nrow=4, ncol=2, byrow = TRUE) rDiscrete(n=2,pf=p) # or pf would be entered as a three dimensional array: p = array(c(0.23,0.11,0.05,0.03,0.31,0.03,0.22,0.02), dim=c(2,2,2)) rDiscrete(n=2,pf=p) ```

rTableICC documentation built on May 15, 2018, 9:03 a.m.