dbeta4: The 4-Parameter Beta Distribution in Regression...

In betareg: Beta Regression

The 4-Parameter Beta Distribution in Regression Parameterization

Description

Density, distribution function, quantile function, and random generation for the 4-parameter beta distribution in regression parameterization.

Usage

dbeta4(x, mu, phi, theta1 = 0, theta2 = 1 - theta1, log = FALSE)

pbeta4(q, mu, phi, theta1 = 0, theta2 = 1 - theta1, lower.tail = TRUE, log.p = FALSE)

qbeta4(p, mu, phi, theta1 = 0, theta2 = 1 - theta1, lower.tail = TRUE, log.p = FALSE)

rbeta4(n, mu, phi, theta1 = 0, theta2 = 1 - theta1)

Arguments

x, q	numeric. Vector of quantiles.
p	numeric. Vector of probabilities.
n	numeric. Number of observations. If length(n) > 1, the length is taken to be the number required.
mu	numeric. The mean of the beta distribution that is extended to support [theta1, theta2].
phi	numeric. The precision parameter of the beta distribution that is extended to support [theta1, theta2].
theta1, theta2	numeric. The minimum and maximum, respectively, of the 4-parameter beta distribution. By default a symmetric support is chosen by theta2 = 1 - theta1 which reduces to the classic beta distribution because of the default theta1 = 0.
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].

Details

The distribution is obtained by a linear transformation of a beta-distributed random variable with intercept theta1 and slope theta2 - theta1.

Value

dbeta4 gives the density, pbeta4 gives the distribution function, qbeta4 gives the quantile function, and rbeta4 generates random deviates.

See Also

dbetar, Beta4

betareg documentation built on July 30, 2025, 3 p.m.