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simEd (version 2.0.1)

vcauchy: Variate Generation for Cauchy Distribution

Description

Variate Generation for Cauchy Distribution

Usage

vcauchy(
  n,
  location = 0,
  scale = 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 Cauchy random variates

quantile

Parameterized quantile function

text

Parameterized title of distribution

Arguments

n

number of observations

location

Location parameter (default 0)

scale

Scale parameter (default 1)

stream

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

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 Cauchy distribution.

Cauchy 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::qcauchy is used to invert the uniform(0,1) variate(s). In this way, using vcauchy 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 Cauchy distribution has density
\deqn{f(x) = \frac{1}{\pi s} \ \left(1 + \left( \frac{x - l}{s} \right)^2
              \right)^{-1}}{
          f(x) = 1 / (\pi s (1 + ((x-l)/s)^2))}

for all \(x\).

The mean is \(a/(a+b)\) and the variance is \(ab/((a+b)^2 (a+b+1))\).

See Also

Examples

Run this code
 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qcauchy
 vcauchy(3, location = 3, scale = 1)

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

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

 set.seed(8675309)
 variates <- vcauchy(100, 0, 3, stream = 1)
 set.seed(8675309)
 variates <- vcauchy(100, 0, 3, stream = 1, antithetic = TRUE)

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