R/RcppExports.R

In lddmm: Longitudinal Drift-Diffusion Mixed Models (LDDMM)

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

hb_log_target <- function(s, z_all, Z, z_s, beta_mu, beta_b, flexible, rows_by_block, tau, delta_t, dec, lmu_re, lb_fix, lb_re, logQ_C, logQ_I, logpi0_C, logpi0_I, sigma2_mu, sigma2_b, mu0_mu, s20_mu, mu0_b, s20_b, tau2) {
    .Call(`_lddmm_hb_log_target`, s, z_all, Z, z_s, beta_mu, beta_b, flexible, rows_by_block, tau, delta_t, dec, lmu_re, lb_fix, lb_re, logQ_C, logQ_I, logpi0_C, logpi0_I, sigma2_mu, sigma2_b, mu0_mu, s20_mu, mu0_b, s20_b, tau2)
}

hb_update_stimulus <- function(s, z_all, Z, beta_mu, beta_b, flexible, rows_by_block, tau, delta_t, dec, lmu_re, lb_fix, lb_re, logQ_C, logQ_I, logpi0_C, logpi0_I, sigma2_mu, sigma2_b, mu0_mu, s20_mu, mu0_b, s20_b, tau2, informed, drop_norm = FALSE, simple_prior = FALSE) {
    .Call(`_lddmm_hb_update_stimulus`, s, z_all, Z, beta_mu, beta_b, flexible, rows_by_block, tau, delta_t, dec, lmu_re, lb_fix, lb_re, logQ_C, logQ_I, logpi0_C, logpi0_I, sigma2_mu, sigma2_b, mu0_mu, s20_mu, mu0_b, s20_b, tau2, informed, drop_norm, simple_prior)
}

#' Log-likelihood of each observation
#'
#' Log-likelihood of the inverse Gaussian race model for every observation,
#' including the contribution of censored observations.
#'
#' @param tau vector of size n containing the response times
#' @param mu matrix of size (n x d1) containing the drift parameters
#' corresponding to the n response times for each possible d1 decision
#' @param b matrix of size (n x d1) containing the boundary parameters
#' corresponding to the n response times for each possible d1 decision
#' @param delta vector of size n containing the offset parameters corresponding
#' to the n response times
#' @param cens vector of size n containing censoring indicators (1 censored, 0
#' not censored) corresponding to the n response times
#' @param D (n x 2) matrix whose first column has the n input stimuli, and whose
#' second column has the n decision categories
#' @return Vector of n log-likelihood values. An uncensored response time that
#' is not larger than its offset has log-likelihood \code{-Inf}.
#' @export
log_likelihood_ind <- function(tau, mu, b, delta, cens, D) {
    .Call(`_lddmm_log_likelihood_ind`, tau, mu, b, delta, cens, D)
}

#' Log-likelihood
#'
#' Log-likelihood of the inverse Gaussian race model (article eq. 2), including
#' the contribution of censored observations.
#'
#' @inheritParams log_likelihood_ind
#' @param log should the result be returned on the log scale?
#' @return The (log-)likelihood of all n observations.
#' @export
log_likelihood <- function(tau, mu, b, delta, cens, D, log) {
    .Call(`_lddmm_log_likelihood`, tau, mu, b, delta, cens, D, log)
}

ll_matrix <- function(tau, delta, dec, log_mu, log_b) {
    .Call(`_lddmm_ll_matrix`, tau, delta, dec, log_mu, log_b)
}

ll_entries <- function(tau, delta, dec, rows, cols, log_mu, log_b) {
    .Call(`_lddmm_ll_entries`, tau, delta, dec, rows, cols, log_mu, log_b)
}

update_delta_cpp <- function(tau, dec, log_mu, log_b, LL, delta, rows_si, delta_max, sd) {
    .Call(`_lddmm_update_delta_cpp`, tau, dec, log_mu, log_b, LL, delta, rows_si, delta_max, sd)
}

update_re_cpp <- function(tau, delta_t, dec, stim, fix, re, log_other, is_drift, LL, U, Bu, rows_ik, Prec, sd, mode) {
    .Call(`_lddmm_update_re_cpp`, tau, delta_t, dec, stim, fix, re, log_other, is_drift, LL, U, Bu, rows_ik, Prec, sd, mode)
}

rinvgauss_cpp <- function(mean, shape) {
    .Call(`_lddmm_rinvgauss_cpp`, mean, shape)
}