Reparameterised beta distribution
beta2.Rd
Density, distribution function, quantile function, and random generation for the beta distribution reparameterised in terms of mean and concentration.
Usage
dbeta2(x, mu, phi, log = FALSE)
pbeta2(q, mu, phi, lower.tail = TRUE, log.p = FALSE)
qbeta2(p, mu, phi, lower.tail = TRUE, log.p = FALSE)
rbeta2(n, mu, phi)
Arguments
- x, q
vector of quantiles
- mu
mean parameter, must be in the interval from 0 to 1.
- phi
concentration parameter, must be positive.
- log, log.p
logical; if
TRUE
, probabilities/ densities \(p\) are returned as \(\log(p)\).- lower.tail
logical; if
TRUE
(default), probabilities are \(P[X \leq x]\), otherwise \(P[X > x]\).- p
vector of probabilities
- n
number of random values to return.
Value
dbeta2
gives the density, pbeta2
gives the distribution function, qbeta2
gives the quantile function, and rbeta2
generates random deviates.
Examples
set.seed(123)
x <- rbeta2(1, 0.5, 1)
d <- dbeta2(x, 0.5, 1)
p <- pbeta2(x, 0.5, 1)
q <- qbeta2(p, 0.5, 1)