The Zero/One-Inflated Beta Distribution

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)

Arguments

x, q, p, n

Same as Beta.

pobs0, pobs1

vector of probabilities that 0 and 1 are observed ($\omega_0$ and $\omega_1$).

shape1, shape2

Same as Beta. They are called a and b in beta respectively.

lower.tail, log, log.p

Same as Beta.

tol

Numeric, tolerance for testing equality with 0 and 1.

Value

dzoabeta gives the density, pzoabeta gives the distribution function, qzoabeta gives the quantile, and rzoabeta generates random deviates.

Author

Xiangjie Xue and T. W. Yee

Details

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.

Examples

if (FALSE) { # \dontrun{
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))
} # }