% Generated by roxygen2: do not edit by hand % Please edit documentation in R/distribution.R \name{distribution} \alias{distribution} \alias{distribution_normal} \alias{distribution_cauchy} \alias{distribution_poisson} \alias{distribution_student} \alias{distribution_chisquared} \alias{distribution_uniform} \alias{distribution_beta} \alias{distribution_custom} \alias{rnorm_perfect} \title{Empirical Distributions} \usage{ distribution(type = "normal", ...) distribution_normal(n, mean = 0, sd = 1, random = FALSE, ...) distribution_cauchy(n, location = 0, scale = 1, random = FALSE, ...) distribution_poisson(n, lambda = 1, random = FALSE, ...) distribution_student(n, df, ncp, random = FALSE, ...) distribution_chisquared(n, df, ncp = 0, random = FALSE, ...) distribution_uniform(n, min = 0, max = 1, random = FALSE, ...) distribution_beta(n, shape1, shape2, ncp = 0, random = FALSE, ...) distribution_custom(n, type = "norm", ..., random = FALSE) rnorm_perfect(n, mean = 0, sd = 1) } \arguments{ \item{type}{Can be \code{"normal"} (default), \code{"cauchy"}, \code{"poisson"}, \code{"chisquared"}, \code{"uniform"}, \code{"student"} or \code{"beta"}.} \item{...}{Arguments passed to or from other methods.} \item{n}{number of observations. If \code{length(n) > 1}, the length is taken to be the number required.} \item{mean}{vector of means.} \item{sd}{vector of standard deviations.} \item{random}{Generate near-perfect or random (simple wrappers for the base R \code{r*} functions) distributions.} \item{location}{location and scale parameters.} \item{scale}{location and scale parameters.} \item{lambda}{vector of (non-negative) means.} \item{df}{degrees of freedom (\eqn{> 0}, maybe non-integer). \code{df = Inf} is allowed.} \item{ncp}{non-centrality parameter \eqn{\delta}{delta}; currently except for \code{rt()}, only for \code{abs(ncp) <= 37.62}. If omitted, use the central t distribution.} \item{min}{lower and upper limits of the distribution. Must be finite.} \item{max}{lower and upper limits of the distribution. Must be finite.} \item{shape1}{non-negative parameters of the Beta distribution.} \item{shape2}{non-negative parameters of the Beta distribution.} } \description{ Generate a sequence of n-quantiles, i.e., a sample of size \code{n} with a near-perfect distribution. } \examples{ library(bayestestR) x <- distribution(n = 10) plot(density(x)) }