The Zero and/or OneInflated Beta Distribution in Regression Parameterization
Description
Density, distribution function, quantile function, and random generation for the zero and/or oneinflated beta distribution in regression parameterization.
Usage
dbeta01(x, mu, phi, p0 = 0, p1 = 0, log = FALSE)
pbeta01(q, mu, phi, p0 = 0, p1 = 0, lower.tail = TRUE, log.p = FALSE)
qbeta01(p, mu, phi, p0 = 0, p1 = 0, lower.tail = TRUE, log.p = FALSE)
rbeta01(n, mu, phi, p0 = 0, p1 = 0)
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 (on the open unit interval). 
phi

numeric. The precision parameter of the beta distribution. 
p0

numeric. The probability for an observation of zero (often referred to as zero inflation). 
p1

numeric. The probability for an observation of one (often referred to as one inflation). 
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 zero and/or oneinflated beta distribution is obtained by adding point masses at zero and/or one to a standard beta distribution.
Note that the support of the standard beta distribution is the open unit interval where values of exactly zero or one cannot occur. Thus, the inflation jargon is rather misleading as there is no probability that could be inflated. It is rather a hurdle or twopart (or threepart) model.
Value
dbeta01
gives the density, pbeta01
gives the distribution function, qbeta01
gives the quantile function, and rbeta01
generates random deviates.
See Also
dbetar
, Beta01