Kumaraswamy function

Kumaraswamy distribution

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

dkumar(x, a = 1, b = 1, log = FALSE)

pkumar(q, a = 1, b = 1, lower.tail = TRUE, log.p = FALSE)

qkumar(p, a = 1, b = 1, lower.tail = TRUE, log.p = FALSE)

rkumar(n, a = 1, b = 1)

Arguments

• x, q: vector of quantiles.

• a, b: positive valued parameters.

• log, log.p: logical; if TRUE, probabilities p are given as log(p).

• lower.tail: logical; if TRUE (default), probabilities are $P[X \le x]$

  otherwise, $P[X > x]$.

• p: vector of probabilities.

• n: number of observations. If length(n) > 1, the length is taken to be the number required.

Details

Probability density function

Cumulative distribution function

Quantile function

Examples

x <- rkumar(1e5, 5, 16)
hist(x, 100, freq = FALSE)
curve(dkumar(x, 5, 16), 0, 1, col = "red", add = TRUE)
hist(pkumar(x, 5, 16))
plot(ecdf(x))
curve(pkumar(x, 5, 16), 0, 1, col = "red", lwd = 2, add = TRUE)

References

Jones, M. C. (2009). Kumaraswamy's distribution: A beta-type distribution with some tractability advantages. Statistical Methodology, 6, 70-81.

Cordeiro, G.M. and de Castro, M. (2009). A new family of generalized distributions. Journal of Statistical Computation & Simulation, 1-17.