Density, distribution function, quantile function, and random generation for the beta distribution in regression parameterization.
dbetar(x, mu, phi, log = FALSE)pbetar(q, mu, phi, lower.tail = TRUE, log.p = FALSE)
qbetar(p, mu, phi, lower.tail = TRUE, log.p = FALSE)
rbetar(n, mu, phi)
dbetar
gives the density, pbetar
gives the distribution
function, qbetar
gives the quantile function, and rbetar
generates random deviates.
numeric. Vector of quantiles.
numeric. Vector of probabilities.
numeric. Number of observations. If length(n) > 1
, the length is
taken to be the number required.
numeric. The mean of the beta distribution.
numeric. The precision parameter of the beta distribution.
logical. If TRUE, probabilities p are given as log(p).
logical. If TRUE (default), probabilities are P[X <= x] otherwise, P[X > x].
This is the reparameterization of the beta distribution with mean mu
and precision phi
, as employed in beta regression. The classic
parameterization of the beta distribution is obtained by setting
shape1 = mu * phi
and shape2 = (1 - mu) * phi
,
respectively.
dbeta
, BetaR