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Type: Package
Title: The Chi Distribution
Version: 0.1
URL: https://github.com/dkahle/chi
BugReports: https://github.com/dkahle/chi/issues
Description: Light weight implementation of the standard distribution functions for the chi distribution, wrapping those for the chi-squared distribution in the stats package.
License: GPL-2
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-05-07 03:05:30 UTC; david_kahle
Author: David Kahle [aut, cre, cph]
Maintainer: David Kahle <david.kahle@gmail.com>
Repository: CRAN
Date/Publication: 2017-05-07 05:22:54 UTC

The Chi Distribution

Description

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

Usage

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

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

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

rchi(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.

Details

The functions (d/p/q/r)chi simply wrap those of the standard (d/p/q/r)chisq R implementation, so look at, say, dchisq for details.

See Also

dchisq; these functions just wrap the (d/p/q/r)chisq functions.

Examples


s <- seq(0, 5, .01)
plot(s, dchi(s, 7), type = 'l')

f <- function(x) dchi(x, 7)
q <- 2
integrate(f, 0, q)
(p <- pchi(q, 7))
qchi(p, 7) # = q
mean(rchi(1e5, 7) <= q)


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



The Inverse 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")


These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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