% File src/library/stats/man/Beta.Rd % Part of the R package, https://www.R-project.org % Copyright 1995-2023 R Core Team % Distributed under GPL 2 or later \name{Beta} \alias{Beta} \alias{dbeta} \alias{pbeta} \alias{qbeta} \alias{rbeta} \title{The Beta Distribution} \concept{incomplete beta function} \description{ Density, distribution function, quantile function and random generation for the Beta distribution with parameters \code{shape1} and \code{shape2} (and optional non-centrality parameter \code{ncp}). } \usage{ dbeta(x, shape1, shape2, ncp = 0, log = FALSE) pbeta(q, shape1, shape2, ncp = 0, lower.tail = TRUE, log.p = FALSE) qbeta(p, shape1, shape2, ncp = 0, lower.tail = TRUE, log.p = FALSE) rbeta(n, shape1, shape2, ncp = 0) } \arguments{ \item{x, q}{vector of quantiles.} \item{p}{vector of probabilities.} \item{n}{number of observations. If \code{length(n) > 1}, the length is taken to be the number required.} \item{shape1, shape2}{non-negative parameters of the Beta distribution.} \item{ncp}{non-centrality parameter.} \item{log, log.p}{logical; if TRUE, probabilities p are given as log(p).} \item{lower.tail}{logical; if TRUE (default), probabilities are \eqn{P[X \le x]}, otherwise, \eqn{P[X > x]}.} } \details{ The Beta distribution with parameters \code{shape1} \eqn{= a} and \code{shape2} \eqn{= b} has density \deqn{f(x)=\frac{\Gamma(a+b)}{\Gamma(a)\Gamma(b)}{x}^{a-1} {(1-x)}^{b-1}% }{\Gamma(a+b)/(\Gamma(a)\Gamma(b)) x^(a-1) (1-x)^(b-1)} for \eqn{a > 0}, \eqn{b > 0} and \eqn{0 \le x \le 1} where the boundary values at \eqn{x=0} or \eqn{x=1} are defined as by continuity (as limits). \cr The mean is \eqn{a/(a+b)} and the variance is \eqn{ab/((a+b)^2 (a+b+1))}. If \eqn{a,b > 1}, (or one of them \eqn{=1}), the mode is \eqn{(a-1)/(a+b-2)}. These and all other distributional properties can be defined as limits (leading to point masses at 0, 1/2, or 1) when \eqn{a} or \eqn{b} are zero or infinite, and the corresponding \code{[dpqr]beta()} functions are defined correspondingly. \code{pbeta} is closely related to the incomplete beta function. As defined by \bibcite{Abramowitz and Stegun 6.6.1} \deqn{B_x(a,b) = \int_0^x t^{a-1} (1-t)^{b-1} dt,}{ B_x(a,b) = integral_0^x t^(a-1) (1-t)^(b-1) dt,} and 6.6.2 \eqn{I_x(a,b) = B_x(a,b) / B(a,b)} where \eqn{B(a,b) = B_1(a,b)} is the Beta function (\code{\link{beta}}). \eqn{I_x(a,b)} is \code{pbeta(x, a, b)}. The noncentral Beta distribution (with \code{ncp} \eqn{ = \lambda}) is defined (Johnson \abbr{et al.}, 1995, pp.\sspace{}502) as the distribution of \eqn{X/(X+Y)} where \eqn{X \sim \chi^2_{2a}(\lambda)}{X ~ chi^2_2a(\lambda)} and \eqn{Y \sim \chi^2_{2b}}{Y ~ chi^2_2b}. There, \eqn{\chi^2_n(\lambda)}{chi^2_n(\lambda)} is the noncentral chi-squared distribution with \eqn{n} degrees of freedom and non-centrality parameter \eqn{\lambda}, see \link{Chisquare}. } \value{ \code{dbeta} gives the density, \code{pbeta} the distribution function, \code{qbeta} the quantile function, and \code{rbeta} generates random deviates. Invalid arguments will result in return value \code{NaN}, with a warning. The length of the result is determined by \code{n} for \code{rbeta}, and is the maximum of the lengths of the numerical arguments for the other functions. The numerical arguments other than \code{n} are recycled to the length of the result. Only the first elements of the logical arguments are used. } \note{ Supplying \code{ncp = 0} uses the algorithm for the non-central distribution, which is not the same algorithm as when \code{ncp} is omitted. This is to give consistent behaviour in extreme cases with values of \code{ncp} very near zero. } \source{ \itemize{ \item The central \code{dbeta} is based on a binomial probability, using code contributed by Catherine Loader (see \code{\link{dbinom}}) if either shape parameter is larger than one, otherwise directly from the definition. The non-central case is based on the derivation as a Poisson mixture of betas (Johnson \abbr{et al.}, 1995, pp.\sspace{}502--3). \item The central \code{pbeta} for the default (\code{log_p = FALSE}) uses a C translation based on Didonato, A. and Morris, A., Jr, (1992) Algorithm 708: Significant digit computation of the incomplete beta function ratios, \emph{ACM Transactions on Mathematical Software}, \bold{18}, 360--373, \doi{10.1145/131766.131776}. (See also\cr Brown, B. and Lawrence Levy, L. (1994) Certification of algorithm 708: Significant digit computation of the incomplete beta, \emph{ACM Transactions on Mathematical Software}, \bold{20}, 393--397, \doi{10.1145/192115.192155}.) \cr %% We have slightly tweaked the original \dQuote{TOMS 708} algorithm, and enhanced for \code{log.p = TRUE}. For that (log-scale) case, underflow to \code{-Inf} (i.e., \eqn{P = 0}) or \code{0}, (i.e., \eqn{P = 1}) still happens because the original algorithm was designed without log-scale considerations. Underflow to \code{-Inf} now typically signals a \code{\link{warning}}. \item The non-central \code{pbeta} uses a C translation of Lenth, R. V. (1987) Algorithm AS 226: Computing noncentral beta probabilities. \emph{Applied Statistics}, \bold{36}, 241--244, \doi{10.2307/2347558}, incorporating\cr Frick, H. (1990)'s AS R84, \emph{Applied Statistics}, \bold{39}, 311--2, \doi{10.2307/2347780} and\cr Lam, M.L. (1995)'s AS R95, \emph{Applied Statistics}, \bold{44}, 551--2, \doi{10.2307/2986147}. This computes the lower tail only, so the upper tail suffers from cancellation and a warning will be given when this is likely to be significant. \item The central case of \code{qbeta} is based on a C translation of Cran, G. W., K. J. Martin and G. E. Thomas (1977). Remark AS R19 and Algorithm AS 109, \emph{Applied Statistics}, \bold{26}, 111--114, \doi{10.2307/2346887}, and subsequent remarks (AS83 and correction). Enhancements, notably for starting values and switching to a log-scale Newton search, by R Core. \item The central case of \code{rbeta} is based on a C translation of R. C. H. Cheng (1978). Generating beta variates with nonintegral shape parameters. \emph{Communications of the ACM}, \bold{21}, 317--322. } } \references{ Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) \emph{The New S Language}. Wadsworth & Brooks/Cole. Abramowitz, M. and Stegun, I. A. (1972) \emph{Handbook of Mathematical Functions.} New York: Dover. Chapter 6: Gamma and Related Functions. Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) \emph{Continuous Univariate Distributions}, volume 2, especially chapter 25. Wiley, New York. } \seealso{ \link{Distributions} for other standard distributions. \code{\link{beta}} for the Beta function. } \examples{ x <- seq(0, 1, length.out = 21) dbeta(x, 1, 1) pbeta(x, 1, 1) ## Visualization, including limit cases: pl.beta <- function(a,b, asp = if(isLim) 1, ylim = if(isLim) c(0,1.1)) { if(isLim <- a == 0 || b == 0 || a == Inf || b == Inf) { eps <- 1e-10 x <- c(0, eps, (1:7)/16, 1/2+c(-eps,0,eps), (9:15)/16, 1-eps, 1) } else { x <- seq(0, 1, length.out = 1025) } fx <- cbind(dbeta(x, a,b), pbeta(x, a,b), qbeta(x, a,b)) f <- fx; f[fx == Inf] <- 1e100 matplot(x, f, ylab="", type="l", ylim=ylim, asp=asp, main = sprintf("[dpq]beta(x, a=\%g, b=\%g)", a,b)) abline(0,1, col="gray", lty=3) abline(h = 0:1, col="gray", lty=3) legend("top", paste0(c("d","p","q"), "beta(x, a,b)"), col=1:3, lty=1:3, bty = "n") invisible(cbind(x, fx)) } pl.beta(3,1) pl.beta(2, 4) pl.beta(3, 7) pl.beta(3, 7, asp=1) pl.beta(0, 0) ## point masses at {0, 1} pl.beta(0, 2) ## point mass at 0 ; the same as pl.beta(1, Inf) pl.beta(Inf, 2) ## point mass at 1 ; the same as pl.beta(3, 0) pl.beta(Inf, Inf)# point mass at 1/2 } \keyword{distribution}