rDiscrete {rTableICC} | R Documentation |
Generate a Random Data from Discrete Probability Function
Description
Generates random data from a given empirical probability function. It also returns cumulative distribution function corresponding to the entered probability function.
Usage
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 |
cdf |
a vector including cumulative distribution function. |
Author(s)
Haydar Demirhan
Maintainer: Haydar Demirhan <haydar.demirhan@rmit.edu.au>
References
Kroese D.P., Taimre T., Botev Z.I. (2011) Handbook of Monte Carlo Methods, Wiley, New York.
Examples
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)
[Package rTableICC version 1.0.9 Index]