| Bernoulli {Rlab} | R Documentation |
Density, distribution function, quantile function and random
generation for the Bernoulli distribution with parameter prob.
dbern(x, prob, log = FALSE) pbern(q, prob, lower.tail = TRUE, log.p = FALSE) qbern(p, prob, lower.tail = TRUE, log.p = FALSE) rbern(n, prob)
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. If length(n) > 1, the length
is taken to be the number required. |
prob |
probability of success on each trial. |
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]. |
The Bernoulli distribution with prob = p has density
p(x) = p^x (1-p)^(1-x)
for x = 0 or 1.
If an element of x is not 0 or 1, the result of dbern
is zero, without a warning.
p(x) is computed using Loader's algorithm, see the reference below.
The quantile is defined as the smallest value x such that F(x) >= p, where F is the distribution function.
dbern gives the density, pbern gives the distribution
function, qbern gives the quantile function and rbern
generates random deviates.
Catherine Loader (2000). Fast and Accurate Computation of Binomial Probabilities; manuscript available from http://cm.bell-labs.com/cm/ms/departments/sia/catherine/dbinom
dbinom for the binomial (Bernoulli is a special case
of the binomial), and dpois for the Poisson distribution.
# Compute P(X=1) for X Bernoulli(0.7) dbern(1, 0.7)