kumarUC: The Kumaraswamy Distribution

In VGAM: Vector Generalized Linear and Additive Models

The Kumaraswamy Distribution

Description

Density, distribution function, quantile function and random generation for the Kumaraswamy distribution.

Usage

dkumar(x, shape1, shape2, log = FALSE)
pkumar(q, shape1, shape2, lower.tail = TRUE, log.p = FALSE)
qkumar(p, shape1, shape2, lower.tail = TRUE, log.p = FALSE)
rkumar(n, shape1, shape2)

Arguments

x, q	vector of quantiles.
p	vector of probabilities.
n	number of observations. If length(n) > 1 then the length is taken to be the number required.
shape1, shape2	positive shape parameters.
log	Logical. If log = TRUE then the logarithm of the density is returned.
lower.tail, log.p	Same meaning as in pnorm or qnorm.

Details

See kumar, the VGAM family function for estimating the parameters, for the formula of the probability density function and other details.

Value

dkumar gives the density, pkumar gives the distribution function, qkumar gives the quantile function, and rkumar generates random deviates.

Author(s)

T. W. Yee and Kai Huang

See Also

kumar.

Examples

## Not run: 
shape1 <- 2; shape2 <- 2; nn <- 201; # shape1 <- shape2 <- 0.5;
x <- seq(-0.05, 1.05, len = nn)
plot(x, dkumar(x, shape1, shape2), type = "l", las = 1, 
     ylab = paste("dkumar(shape1 = ", shape1,
                  ", shape2 = ", shape2, ")"),
     col = "blue", cex.main = 0.8, ylim = c(0,1.5),
     main = "Blue is density, orange is the CDF",
     sub = "Red lines are the 10,20,...,90 percentiles")
lines(x, pkumar(x, shape1, shape2), col = "orange")
probs <- seq(0.1, 0.9, by = 0.1)
Q <- qkumar(probs, shape1, shape2)
lines(Q, dkumar(Q, shape1, shape2), col = "red", lty = 3, type = "h")
lines(Q, pkumar(Q, shape1, shape2), col = "red", lty = 3, type = "h")
abline(h = probs, col = "red", lty = 3)
max(abs(pkumar(Q, shape1, shape2) - probs))  # Should be 0

## End(Not run)

VGAM documentation built on Sept. 18, 2024, 9:09 a.m.