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#' Apply Gamma distribution to sample and compute required components for the test.
#'
#' @description Compute Maximum likelihood estimates of the parameters in Gamma distribution, Score function evaluated at the sample,
#' and probability inverse transformed (PIT) values of sample.
#'
#' @param x a numeric vector.
#'
#' @param use.rate logical. If \code{TRUE} the rate parameter is returned while estimating MLE. Otherwise the scale is returned.
#'
#' @return a list with three elements.
#'
applyGamma = function(x, use.rate){
# Compute MLE of parameters in Gamma distribution
par <- gammaMLE(x, ur = use.rate)
# Compute score function for sample
S <- gammaScore(x = x, theta = par)
# Compute the probability inverse transfer of sample
pit <- gammaPIT(x = x, theta = par)
# Define the list to return
res <- list(Score = S, pit = pit, par = par)
return(res)
}
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