R/common-arguments.R

In LambertW: Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, Skewed Data

#' @title Common arguments for several functions
#' @name common-arguments
#' 
#' @description
#' Reference list of most common function arguments in this package.
#' 
#' @param y a numeric vector of real values (the observed data).
#' @param distname character; name of input distribution; see
#'     \code{\link{get_distnames}}.
#' @param type type of Lambert W \eqn{\times} F distribution: skewed \code{"s"};
#'     heavy-tail \code{"h"}; or skewed heavy-tail \code{"hh"}.
#' @param theta list; a (possibly incomplete) list of parameters \code{alpha},
#'     \code{beta}, \code{gamma}, \code{delta}. \code{\link{complete_theta}}
#'     fills in default values for missing entries.
#' @param beta numeric vector (deprecated); parameter \eqn{\boldsymbol \beta} of
#'     the input distribution.  See \code{\link{check_beta}} on how to specify
#'     \code{beta} for each distribution.
#' @param gamma scalar (deprecated); skewness parameter; default: \code{0}.
#' @param delta scalar or vector (length 2) (deprecated); heavy-tail
#'     parameter(s); default: \code{0}.
#' @param alpha scalar or vector (length 2) (deprecated); heavy tail
#'     exponent(s); default: \code{1}.
#' @param tau named vector \eqn{\tau} which defines the variable transformation.
#'     Must have at least \code{'mu_x'} and \code{'sigma_x'} element; see
#'     \code{\link{complete_tau}} for details.
#' @param return.u logical; if \code{TRUE}, it returns the standardized input
#'     that corresponds to \eqn{U}, which is the zero-mean and/or unit-variance
#'     version of input \eqn{X \sim F_X}.
#' @param use.mean.variance logical; if \code{TRUE} it uses mean and variance
#'     implied by \eqn{\boldsymbol \beta} to do the transformation (Goerg 2011).
#'     If \code{FALSE}, it uses the alternative definition from Goerg (2016)
#'     with location and scale parameter.
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