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simEd (version 2.0.1)

vunif: Variate Generation for Uniform Distribution

Description

Variate Generation for Uniform Distribution

Usage

vunif(n, min = 0, max = 1, stream = NULL, antithetic = FALSE, asList = FALSE)

Value

If asList is FALSE (default), return a vector of random variates.

Otherwise, return a list with components suitable for visualizing inversion, specifically:

u

A vector of generated U(0,1) variates

x

A vector of uniform random variates

quantile

Parameterized quantile function

text

Parameterized title of distribution

Arguments

n

number of observations

min

lower limit of distribution (default 0)

max

upper limit of distribution (default 1)

stream

if NULL (default), uses stats::runif to generate uniform variates; otherwise, an integer in 1:25 indicates the rstream stream from which to generate uniform variates;

antithetic

if FALSE (default), inverts \(u\) = uniform(0,1) variate(s) generated via either stats::runif or rstream::rstream.sample; otherwise, uses \(1 - u\)

asList

if FALSE (default), output only the generated random variates; otherwise, return a list with components suitable for visualizing inversion. See return for details

Author

Barry Lawson (blawson@bates.edu),
Larry Leemis (leemis@math.wm.edu),
Vadim Kudlay (vkudlay@nvidia.com)

Details

Generates random variates from the uniform distribution.

Uniform variates are generated by inverting uniform(0,1) variates produced either by stats::runif (if stream is NULL) or by rstream::rstream.sample (if stream is not NULL). In either case, stats::qunif is used to invert the uniform(0,1) variate(s). In this way, using vunif provides a monotone and synchronized binomial variate generator, although not particularly fast.

The stream indicated must be an integer between 1 and 25 inclusive.

The uniform distribution has density

      \deqn{f(x) = \frac{1}{max-min}}{
                f(x) = 1/(max-min)}

for \(min \le x \le max\).

See Also

Examples

Run this code
 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qunif
 vunif(3, min = -2, max = 2)

 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qunif
 vunif(3, 0, 10, stream = 1)
 vunif(3, 0, 10, stream = 2)

 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qunif
 vunif(1, 0, 10, stream = 1)
 vunif(1, 0, 10, stream = 2)
 vunif(1, 0, 10, stream = 1)
 vunif(1, 0, 10, stream = 2)
 vunif(1, 0, 10, stream = 1)
 vunif(1, 0, 10, stream = 2)

 set.seed(8675309)
 variates <- vunif(100, 0, 10, stream = 1)
 set.seed(8675309)
 variates <- vunif(100, 0, 10, stream = 1, antithetic = TRUE)

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