invchi: The Inverse Chi Distribution

In dkahle/chi: The Chi Distribution

Description

Density, distribution function, quantile function and random generation for the inverse chi distribution.

Usage

dinvchi(x, df, ncp = 0, log = FALSE)

pinvchi(q, df, ncp = 0, lower.tail = TRUE, log.p = FALSE)

qinvchi(p, df, ncp = 0, lower.tail = TRUE, log.p = FALSE)

rinvchi(n, df, ncp = 0)

Arguments

x, q	vector of quantiles.
df	degrees of freedom (non-negative, but can be non-integer).
ncp	non-centrality parameter (non-negative).
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.

See Also

dchi

Examples

s <- seq(0, 2, .01)
plot(s, dinvchi(s, 7), type = 'l')

f <- function(x) dinvchi(x, 7)
q <- .5
integrate(f, 0, q)
(p <- pinvchi(q, 7))
qinvchi(p, 7) # = q
mean(rinvchi(1e5, 7) <= q)


samples <- rinvchi(1e5, 7)
plot(density(samples))
curve(f, add = TRUE, col = "red")

dkahle/chi documentation built on May 15, 2019, 9:07 a.m.