R/RcppExports.R In melt: Multiple Empirical Likelihood Tests

Documented in el_mean

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

ELtest <- function(x, c, lhs, rhs, threshold, maxit = 1e4L, abstol = 1e-8) {
.Call(_melt_ELtest, x, c, lhs, rhs, threshold, maxit, abstol)
}

#' Empirical likelihood test for mean
#'
#' Computes empirical likelihood for mean parameter.
#'
#' @param theta Numeric vector of parameters to be tested.
#' @param x Numeric matrix or vector of data. If \code{x} is a matrix, each row corresponds to an observation.
#' @param maxit Maximum number of iterations for optimization. Defaults to 50.
#' @param abstol Absolute convergence tolerance for optimization. Defaults to 1e-08.
#'
#' @return A list with class \code{c("mean", "melt")}.
#' @references Owen, A. B. (1988), Empirical Likelihood for Linear Models," \emph{The Annals of Statistics}, 1725–1747.
#' @examples
#' ## scalar mean
#' theta <- 0
#' x <- rnorm(100)
#' el_mean(theta, x)
#'
#' ## vector mean
#' x <- matrix(rnorm(100), ncol = 2)
#' theta <- c(0, 0)
#' el_mean(theta, x)
#'
#' @export
el_mean <- function(theta, x, maxit = 50L, abstol = 1e-8) {
.Call(_melt_el_mean, theta, x, maxit, abstol)
}

pairwise <- function(x, c, control = 0L, k = 1L, level = 0.05, interval = TRUE, method = "AMC", B = 1e4L, nthread = 1L, progress = TRUE, threshold = 50, maxit = 1e4L, abstol = 1e-8) {
.Call(_melt_pairwise, x, c, control, k, level, interval, method, B, nthread, progress, threshold, maxit, abstol)
}

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melt documentation built on Dec. 22, 2021, 9:06 a.m.