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#' Computes the Deflated Relative Occurrences
#'
#' Computes the vector of deflated relative occurrences for all variables (i.e., j = 1,..., p) and T = T_stop.
#'
#' @param p Number of candidate variables.
#' @param T_stop Number of included dummies after which the random experiments (i.e., forward selection processes) are stopped.
#' @param num_dummies Number of dummies
#' @param phi_T_mat Matrix of relative occurrences for all variables (i.e., j = 1,..., p) and for T = 1, ..., T_stop.
#' @param Phi Vector of relative occurrences for all variables (i.e., j = 1,..., p) at T = T_stop.
#' @param eps Numerical zero.
#'
#' @return Vector of deflated relative occurrences for all variables (i.e., j = 1,..., p) and T = T_stop.
Phi_prime_fun <- function(p,
T_stop,
num_dummies,
phi_T_mat,
Phi,
eps = .Machine$double.eps) {
av_num_var_sel <- colSums(phi_T_mat)
fifty_phi_T_mat <- phi_T_mat[Phi > 0.5, , drop = FALSE]
delta_av_num_var_sel <- colSums(fifty_phi_T_mat)
if (T_stop > 1) {
delta_av_num_var_sel[2:T_stop] <- delta_av_num_var_sel[2:T_stop] - delta_av_num_var_sel[1:(T_stop - 1)]
phi_T_mat[, 2:T_stop] <- phi_T_mat[, 2:T_stop] - phi_T_mat[, 1:(T_stop - 1)]
}
phi_scale <- rep(NA, times = length(delta_av_num_var_sel))
for (t in seq_along(delta_av_num_var_sel)) {
if (delta_av_num_var_sel[t] > eps) {
phi_scale[t] <- 1 - (((p - av_num_var_sel[t]) / (num_dummies - t + 1)) / delta_av_num_var_sel[t])
} else {
phi_scale[t] <- 0
}
}
Phi_prime <- phi_T_mat %*% phi_scale
return(Phi_prime)
}
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