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simEd (version 2.0.1)

vexp: Variate Generation for Exponential Distribution

Description

Variate Generation for Exponential Distribution

Usage

vexp(n, rate = 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 exponential random variates

quantile

Parameterized quantile function

text

Parameterized title of distribution

Arguments

n

number of observations

rate

Rate of distribution (default 1)

stream

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

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 exponential distribution.

Exponential 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::qexp is used to invert the uniform(0,1) variate(s). In this way, using vexp 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 exponential distribution with rate \eqn{\lambda} has density

\deqn{f(x) = \lambda e^{-\lambda x}}{ f(x) = \lambda e^(-\lambda x)}

for \eqn{x \geq 0}.

See Also

Examples

Run this code
 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qexp
 vexp(3, rate = 2)

 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qexp
 vexp(3, 2, stream = 1)
 vexp(3, 2, stream = 2)

 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qexp
 vexp(1, 2, stream = 1)
 vexp(1, 2, stream = 2)
 vexp(1, 2, stream = 1)
 vexp(1, 2, stream = 2)
 vexp(1, 2, stream = 1)
 vexp(1, 2, stream = 2)

 set.seed(8675309)
 variates <- vexp(100, 2, stream = 1)
 set.seed(8675309)
 variates <- vexp(100, 2, stream = 1, antithetic = TRUE)

 set.seed(8675309)
 # NOTE: Default functions for M/M/1 ssq(), ignoring fixed n
 interarrivals <- vexp(1000, rate = 1,    stream = 1)
 services      <- vexp(1000, rate = 10/9, stream = 2)

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