log, log.p: logical; if TRUE, probabilities p are given as log(p).
lower.tail: logical; if TRUE (default), probabilities are P[X≤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
f(x)=αββxβ−1f(x)=(β∗x(β−1))/(αβ)
Cumulative distribution function
F(x)=αβxβF(x)=xβ/αβ
Quantile function
F−1(p)=αp1/βF−1(p)=α∗p(1/β)
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)