The Geometric Distribution

Usage

dgeom(x, prob)
pgeom(q, prob)
qgeom(p, prob)
rgeom(n, prob)

Arguments

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 to generate.
prob probability of success in each trial.

Value

These functions provide information about the geometric distribution with parameter prob. dgeom gives the density, pgeom gives the distribution function, qgeom gives the quantile function, and rgeom generates random deviates.

The geometric distribution with prob = p has density

p(x) = p (1-p)^x

for x = 0, 1, 2, ...

See Also

dnbinom for the negative binomial which generalizes the geometric distribution.

Examples

pp <- sort(c((1:9)/10, 1 - .2^(2:8)))
print(qg <- qgeom(pp, prob = .2))
for(i in 1:2) print(qg <- qgeom(pgeom(qg, prob=.2), prob =.2))
Ni <- rgeom(20, prob = 1/4); table(factor(Ni, 0:max(Ni)))


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