Geometric {stats} | R Documentation |
Density, distribution function, quantile function and random
generation for the geometric distribution with parameter prob
.
dgeom(x, prob, log = FALSE)
pgeom(q, prob, lower.tail = TRUE, log.p = FALSE)
qgeom(p, prob, lower.tail = TRUE, log.p = FALSE)
rgeom(n, prob)
x , q |
vector of quantiles representing the number of failures in a sequence of Bernoulli trials before success occurs. |
p |
vector of probabilities. |
n |
number of observations. If |
prob |
probability of success in each trial. |
log , log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are
|
The geometric distribution with prob
= p
has density
p(x) = p {(1-p)}^{x}
for x = 0, 1, 2, \ldots
, 0 < p \le 1
.
If an element of x
is not integer, the result of pgeom
is zero, with a warning.
The quantile is defined as the smallest value x
such that
F(x) \ge p
, where F
is the distribution function.
dgeom
gives the density,
pgeom
gives the distribution function,
qgeom
gives the quantile function, and
rgeom
generates random deviates.
Invalid prob
will result in return value NaN
, with a warning.
dgeom
computes via dbinom
, using code contributed by
Catherine Loader (see dbinom
).
pgeom
and qgeom
are based on the closed-form formulae.
rgeom
uses the derivation as an exponential mixture of Poissons, see
Devroye, L. (1986) Non-Uniform Random Variate Generation. Springer-Verlag, New York. Page 480.
dnbinom
for the negative binomial which generalizes
the geometric distribution.
qgeom((1:9)/10, prob = .2)
Ni <- rgeom(20, prob = 1/4); table(factor(Ni, 0:max(Ni)))