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#' Choosing the truncation level for the NGG process
#'
#' This function uses the M_array which provides the threshold which ensures
#' a moment match of 5% for NGG parameters alpha, kappa, gama
#'
#' For internal use
#'
#' @param alpha Numeric constant. Total mass of the centering measure
#' @param kappa Numeric positive constant.
#' @param gama Numeric constant. \eqn{0 \leq Gama \leq 1}{0 <= Gama <=1}.
#' @param max_threshold Numeric positive integer. Maximum allowed value for the threshold
#'
#' @return Numeric positive integer, the truncation level of the NGG process
#'
#' @keywords internal
thresholdGG <-
function(alpha = 1, kappa = 1, gama = 1 / 2, max_threshold = 200) {
alpha_vect <- c(.1, 1, 5, 20) # mass param
kappa_vect <- c(.1, 1, 5, 20)
gama_vect <- c(0, .2, .4, .6)
alpha_index <- which.max(alpha_vect >= alpha)
kappa_index <- which.max(kappa_vect >= kappa)
gama_index <- which.max(gama_vect >= gama)
M <- M_array[alpha_index, kappa_index, gama_index]
# if we are out of the grid, we assign the max_threshold
out_of_grid <- (prod(1 - (alpha_vect >= alpha)) |
prod(1 - (kappa_vect >= kappa)) |
prod(1 - (gama_vect >= gama)))
if (out_of_grid) {
M <- max_threshold
}
return(M)
}
globalVariables(names = c("M_array"))
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