R/chi.R In chi: The Chi Distribution

Documented in dchipchiqchirchi

```#' The Chi Distribution
#'
#' Density, distribution function, quantile function and random
#' generation for the chi distribution.
#'
#' The functions (d/p/q/r)chi simply wrap those of the standard
#' (d/p/q/r)chisq R implementation, so look at, say,
#'
#'
#' @param x,q vector of quantiles.
#' @param p vector of probabilities.
#' @param n number of observations. If length(n) > 1, the length is
#'   taken to be the number required.
#' @param df degrees of freedom (non-negative, but can be
#'   non-integer).
#' @param ncp non-centrality parameter (non-negative).
#' @param log,log.p logical; if TRUE, probabilities p are given as
#'   log(p).
#' @param lower.tail logical; if TRUE (default), probabilities are
#'   P[X <= x] otherwise, P[X > x].
#' @seealso \code{\link{dchisq}}; these functions just wrap the
#'   (d/p/q/r)chisq functions.
#' @name chi
#' @importFrom stats dchisq pchisq qchisq rchisq
#' @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")
#'
#'
NULL

#' @rdname chi
#' @export
dchi <- function(x, df, ncp = 0, log = FALSE) {
log_f <- dchisq(x^2, df, ncp, log = TRUE) + log(2) + log(x)
if(log) return(log_f)
exp(log_f)
}

#' @rdname chi
#' @export
pchi <- function(q, df, ncp = 0, lower.tail = TRUE, log.p = FALSE) {
pchisq(q^2, df, ncp, lower.tail, log.p)
}

#' @rdname chi
#' @export
qchi <- function(p, df, ncp = 0, lower.tail = TRUE, log.p = FALSE) {
sqrt( qchisq(p, df, ncp, lower.tail, log.p) )
}

#' @rdname chi
#' @export
rchi <- function(n, df, ncp = 0) {
sqrt( rchisq(n, df, ncp) )
}
```

Try the chi package in your browser

Any scripts or data that you put into this service are public.

chi documentation built on May 30, 2017, 5:19 a.m.