| 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
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")