Zoabeta {VGAM} | R Documentation |
The Zero/One-Inflated Beta Distribution
Description
Density, distribution function, and random generation for the zero/one-inflated beta distribution.
Usage
dzoabeta(x, shape1, shape2, pobs0 = 0, pobs1 = 0, log = FALSE,
tol = .Machine$double.eps)
pzoabeta(q, shape1, shape2, pobs0 = 0, pobs1 = 0,
lower.tail = TRUE, log.p = FALSE, tol = .Machine$double.eps)
qzoabeta(p, shape1, shape2, pobs0 = 0, pobs1 = 0,
lower.tail = TRUE, log.p = FALSE, tol = .Machine$double.eps)
rzoabeta(n, shape1, shape2, pobs0 = 0, pobs1 = 0,
tol = .Machine$double.eps)
Arguments
x , q , p , n |
Same as |
pobs0 , pobs1 |
vector of probabilities that 0 and 1 are observed
( |
shape1 , shape2 |
|
lower.tail , log , log.p |
Same as |
tol |
Numeric, tolerance for testing equality with 0 and 1. |
Details
This distribution is a mixture of a discrete distribution
with a continuous distribution.
The cumulative distribution function of is
where is the cumulative distribution function
of the beta distribution with the same shape parameters
(
pbeta
),
is the inflated probability at 0 and
is the inflated probability at 1.
The default values of
mean that these
functions behave like the ordinary
Beta
when only the essential arguments are inputted.
Value
dzoabeta
gives the density,
pzoabeta
gives the distribution function,
qzoabeta
gives the quantile, and
rzoabeta
generates random deviates.
Author(s)
Xiangjie Xue and T. W. Yee
See Also
zoabetaR
,
beta
,
betaR
,
Betabinom
.
Examples
## Not run:
N <- 1000; y <- rzoabeta(N, 2, 3, 0.2, 0.2)
hist(y, probability = TRUE, border = "blue", las = 1,
main = "Blue = 0- and 1-altered; orange = ordinary beta")
sum(y == 0) / N # Proportion of 0s
sum(y == 1) / N # Proportion of 1s
Ngrid <- 1000
lines(seq(0, 1, length = Ngrid),
dbeta(seq(0, 1, length = Ngrid), 2, 3), col = "orange")
lines(seq(0, 1, length = Ngrid), col = "blue",
dzoabeta(seq(0, 1, length = Ngrid), 2 , 3, 0.2, 0.2))
## End(Not run)