R/RcppExports.R

In nitayalon/semiparametric_hmm: An implementation a semiparametric HMM

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

rcpp_computeAllProbabilities <- function(observations, theta, p, b) {
    .Call('_semiparametrichmm_rcpp_computeAllProbabilities', PACKAGE = 'semiparametrichmm', observations, theta, p, b)
}

rcpp_backwardVector <- function(observations, transitionMatrix, theta, p, b) {
    .Call('_semiparametrichmm_rcpp_backwardVector', PACKAGE = 'semiparametrichmm', observations, transitionMatrix, theta, p, b)
}

computeCentralDistribution <- function(x, theta, p, b) {
    .Call('_semiparametrichmm_computeCentralDistribution', PACKAGE = 'semiparametrichmm', x, theta, p, b)
}

rcpp_forwardVector <- function(observations, transitionMatrix, theta, p, b) {
    .Call('_semiparametrichmm_rcpp_forwardVector', PACKAGE = 'semiparametrichmm', observations, transitionMatrix, theta, p, b)
}

rcpp_computeNRDenom <- function(x, theta, p, b) {
    .Call('_semiparametrichmm_rcpp_computeNRDenom', PACKAGE = 'semiparametrichmm', x, theta, p, b)
}

rcpp_pointDensity <- function(x, theta, p, b, N) {
    .Call('_semiparametrichmm_rcpp_pointDensity', PACKAGE = 'semiparametrichmm', x, theta, p, b, N)
}

NewtonRaphson <- function(data, theta, p, max_iteration) {
    .Call('_semiparametrichmm_NewtonRaphson', PACKAGE = 'semiparametrichmm', data, theta, p, max_iteration)
}

optimizationTargetFunction <- function(x, theta, p, b) {
    .Call('_semiparametrichmm_optimizationTargetFunction', PACKAGE = 'semiparametrichmm', x, theta, p, b)
}

rcpp_RecursiveBaumWelch <- function(observations, transitionMatrix, theta, p, b) {
    .Call('_semiparametrichmm_rcpp_RecursiveBaumWelch', PACKAGE = 'semiparametrichmm', observations, transitionMatrix, theta, p, b)
}