#' Estimation of Mean Residual Lifetime under RSS
#'
#' Estimation of Mean Residual Lifetime Based on the Ranked Set Sampling Scheme (EMRL_RSS)
#' @name EMRL_RSS
#' @param RSSdata Data generated from Ranked Set Sampling Scheme
#' @param t A numeric vector
#' @param k Collection size
#' @param m Number of cycles
#' @return The Estimation of MRL based on the RSS
#' @examples
#' k <- 5
#' m <- 5
#' lambda <- 1
#' RSSdata <- matrix(0, nrow = k, ncol = m)
#' for (j in 1:m) {
#' for (i in 1:k) {
#' x <- rgamma(k, shape = 2, scale = 1)
#' y <- lambda * ((x - mean(x)) / sd(x)) + sqrt((1 - lambda^2)) * rnorm(k, 0, 1)
#' sy <- sort(y)
#' syindex <- sort(y, index.return = TRUE)$ix
#' RSSdata[i, j] <- x[syindex][i]
#' }
#' }
#' Mhat_RSS(seq(0, 10, 0.1), RSSdata, k = 5, m = 5)
#' @export Mhat_RSS
Mhat_RSS <- function(t, RSSdata, k, m) {
out <- sapply(t, function(x) 1 / k * colSums((Shat_i(x, RSSdata) / Shat(x, c(RSSdata))) * MhatRSS_i(x, RSSdata, k, m)))
return(out)
}
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