vgeom {simEd} | R Documentation |
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 |
stream |
if |
antithetic |
if |
asList |
if |
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
.
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 |
Author(s)
Barry Lawson (blawson@bates.edu),
Larry Leemis (leemis@math.wm.edu),
Vadim Kudlay (vkudlay@nvidia.com)
See Also
rstream
, set.seed
,
stats::runif
Examples
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(100, 0.3, stream = 1)
set.seed(8675309)
variates <- vgeom(100, 0.3, stream = 1, antithetic = TRUE)