simEd (version 2.0.0)

vgeom: Variate Generation for Geometric Distribution

Description

Variate Generation for Geometric Distribution

Usage

vgeom(n, prob, stream = NULL, antithetic = FALSE, asList = FALSE)

Arguments

n

number of observations

prob

Probability of success in each trial (0 \(<\) prob \(\le\) 1)

stream

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

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

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 geometric random variates

quantile

Parameterized quantile function

text

Parameterized title of distribution

Details

Generates random variates from the geometric distribution.

Geometric 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::qgeom is used to invert the uniform(0,1) variate(s). In this way, using vgeom 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 geometric distribution with parameter prob = \(p\) has density $$p(x) = p (1-p)^x$$ for \(x = 0, 1, 2, \ldots\), where \(0 < p \le 1\).

See Also

rstream, set.seed, stats::runif

stats::rgeom

Examples

# NOT RUN {
 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qgeom
 vgeom(3, prob = 0.3)

 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qgeom
 vgeom(3, 0.3, stream = 1)
 vgeom(3, 0.3, stream = 2)

 set.seed(8675309)
 # NOTE: following inverts rstream::rstream.sample using stats::qgeom
 vgeom(1, 0.3, stream = 1)
 vgeom(1, 0.3, stream = 2)
 vgeom(1, 0.3, stream = 1)
 vgeom(1, 0.3, stream = 2)
 vgeom(1, 0.3, stream = 1)
 vgeom(1, 0.3, stream = 2)

 set.seed(8675309)
 variates <- vgeom(1000, 0.3, stream = 1)
 set.seed(8675309)
 variates <- vgeom(1000, 0.3, stream = 1, antithetic = TRUE)

# }