PowerDist function

Power distribution

Power distribution

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

dpower(x, alpha, beta, log = FALSE) ppower(q, alpha, beta, lower.tail = TRUE, log.p = FALSE) qpower(p, alpha, beta, lower.tail = TRUE, log.p = FALSE) rpower(n, alpha, beta)

Arguments

  • x, q: vector of quantiles.

  • alpha, beta: parameters.

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

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

    otherwise, P[X>x]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

f(x)=βxβ1αβf(x)=(βx(β1))/(αβ) f(x) = \frac{\beta x^{\beta-1}}{\alpha^\beta}f(x) = (\beta*x^(\beta-1)) / (\alpha^\beta)

Cumulative distribution function

F(x)=xβαβF(x)=xβ/αβ F(x) = \frac{x^\beta}{\alpha^\beta}F(x) = x^\beta / \alpha^\beta

Quantile function

F1(p)=αp1/βF1(p)=αp(1/β) F^{-1}(p) = \alpha p^{1/\beta}F^-1(p) = \alpha * p^(1/\beta)

Examples

x <- rpower(1e5, 5, 16) hist(x, 100, freq = FALSE) curve(dpower(x, 5, 16), 2, 6, col = "red", add = TRUE, n = 5000) hist(ppower(x, 5, 16)) plot(ecdf(x)) curve(ppower(x, 5, 16), 2, 6, col = "red", lwd = 2, add = TRUE)
  • Maintainer: Tymoteusz Wolodzko
  • License: GPL-2
  • Last published: 2023-11-30