Zoabeta | R Documentation |
Density, distribution function, and random generation for the zero/one-inflated beta distribution.
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)
x , q , p , n |
Same as |
pobs0 , pobs1 |
vector of probabilities that 0 and 1 are observed
( |
shape1 , shape2 |
Same as |
lower.tail , log , log.p |
Same as |
tol |
Numeric, tolerance for testing equality with 0 and 1. |
This distribution is a mixture of a discrete distribution
with a continuous distribution.
The cumulative distribution function of Y
is
F(y) =(1 - \omega_0 -\omega_1) B(y) +
\omega_0 \times I[0 \leq y] +
\omega_1 \times I[1 \leq y]
where B(y)
is the cumulative distribution function
of the beta distribution with the same shape parameters
(pbeta
),
\omega_0
is the inflated probability at 0 and
\omega_1
is the inflated probability at 1.
The default values of \omega_j
mean that these
functions behave like the ordinary Beta
when only the essential arguments are inputted.
dzoabeta
gives the density,
pzoabeta
gives the distribution function,
qzoabeta
gives the quantile, and
rzoabeta
generates random deviates.
Xiangjie Xue and T. W. Yee
zoabetaR
,
beta
,
betaR
,
Betabinom
.
## 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)
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