R/RcppExports.R

In mcemGLM: Maximum Likelihood Estimation for Generalized Linear Mixed Models

# This file was generated by Rcpp::compileAttributes
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

iMatrixDiagGammaCpp_n <- function(beta, sigma, alpha, uSample, kKi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_iMatrixDiagGammaCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, uSample, kKi, kY, kX, kZ, B, sd0)
}

iMatrixDiagGammaCpp_t <- function(beta, sigma, alpha, sigmaType, uSample, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_iMatrixDiagGammaCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, uSample, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0)
}

iMatrixDiagCpp_n <- function(beta, sigma, uSample, kKi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_iMatrixDiagCpp_n', PACKAGE = 'mcemGLM', beta, sigma, uSample, kKi, kY, kX, kZ, B, sd0)
}

iMatrixDiagNegBinomCpp_n <- function(beta, sigma, alpha, uSample, kKi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_iMatrixDiagNegBinomCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, uSample, kKi, kY, kX, kZ, B, sd0)
}

iMatrixDiagNegBinomCpp_t <- function(beta, sigma, alpha, sigmaType, uSample, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_iMatrixDiagNegBinomCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, uSample, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0)
}

iMatrixDiagPoissonCpp_n <- function(beta, sigma, uSample, kKi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_iMatrixDiagPoissonCpp_n', PACKAGE = 'mcemGLM', beta, sigma, uSample, kKi, kY, kX, kZ, B, sd0)
}

iMatrixDiagPoissonCpp_t <- function(beta, sigma, sigmaType, uSample, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_iMatrixDiagPoissonCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, uSample, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0)
}

iMatrixDiagCpp_t <- function(beta, sigma, sigmaType, uSample, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_iMatrixDiagCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, uSample, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0)
}

loglikelihoodGammaGradientCpp_n <- function(beta, sigma, alpha, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodGammaGradientCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, kKi, u, kY, kX, kZ)
}

loglikelihoodGammaGradientCpp_t <- function(beta, sigma, alpha, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodGammaGradientCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodGammaHessianCpp_n <- function(beta, sigma, alpha, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodGammaHessianCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, kKi, u, kY, kX, kZ)
}

loglikelihoodGammaHessianCpp_t <- function(beta, sigma, alpha, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodGammaHessianCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodGammaCpp_n <- function(beta, sigma, alpha, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodGammaCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, kY, kX, kZ)
}

loglikelihoodGammaCpp_t <- function(beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodGammaCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodLogitGradientCpp_n <- function(beta, sigma, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodLogitGradientCpp_n', PACKAGE = 'mcemGLM', beta, sigma, kKi, u, kY, kX, kZ)
}

loglikelihoodLogitGradientCpp_t <- function(beta, sigma, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodLogitGradientCpp_t', PACKAGE = 'mcemGLM', beta, sigma, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodLogitHessianCpp_n <- function(beta, sigma, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodLogitHessianCpp_n', PACKAGE = 'mcemGLM', beta, sigma, kKi, u, kY, kX, kZ)
}

loglikelihoodLogitHessianCpp_t <- function(beta, sigma, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodLogitHessianCpp_t', PACKAGE = 'mcemGLM', beta, sigma, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodLogitCpp_n <- function(beta, sigma, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodLogitCpp_n', PACKAGE = 'mcemGLM', beta, sigma, u, kY, kX, kZ)
}

loglikelihoodLogitCpp_t <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodLogitCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodNegBinomGradientCpp_n <- function(beta, sigma, alpha, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodNegBinomGradientCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, kKi, u, kY, kX, kZ)
}

loglikelihoodNegBinomGradientCpp_t <- function(beta, sigma, alpha, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodNegBinomGradientCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodNegBinomHessianCpp_n <- function(beta, sigma, alpha, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodNegBinomHessianCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, kKi, u, kY, kX, kZ)
}

loglikelihoodNegBinomHessianCpp_t <- function(beta, sigma, alpha, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodNegBinomHessianCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodNegBinomCpp_n <- function(beta, sigma, alpha, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodNegBinomCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, kY, kX, kZ)
}

loglikelihoodNegBinomCpp_t <- function(beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodNegBinomCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodPoissonGradientCpp_n <- function(beta, sigma, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodPoissonGradientCpp_n', PACKAGE = 'mcemGLM', beta, sigma, kKi, u, kY, kX, kZ)
}

loglikelihoodPoissonGradientCpp_t <- function(beta, sigma, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodPoissonGradientCpp_t', PACKAGE = 'mcemGLM', beta, sigma, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodPoissonHessianCpp_n <- function(beta, sigma, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodPoissonHessianCpp_n', PACKAGE = 'mcemGLM', beta, sigma, kKi, u, kY, kX, kZ)
}

loglikelihoodPoissonHessianCpp_t <- function(beta, sigma, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodPoissonHessianCpp_t', PACKAGE = 'mcemGLM', beta, sigma, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

loglikelihoodPoissonCpp_n <- function(beta, sigma, u, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodPoissonCpp_n', PACKAGE = 'mcemGLM', beta, sigma, u, kY, kX, kZ)
}

loglikelihoodPoissonCpp_t <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_loglikelihoodPoissonCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

margloglikelihoodLogitCpp_n <- function(beta, sigma, u, kY, kX, kZ) {
    .Call('mcemGLM_margloglikelihoodLogitCpp_n', PACKAGE = 'mcemGLM', beta, sigma, u, kY, kX, kZ)
}

margloglikelihoodLogitCpp_t <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_margloglikelihoodLogitCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

min0 <- function(a, b) {
    .Call('mcemGLM_min0', PACKAGE = 'mcemGLM', a, b)
}

ldmn <- function(x, sigma) {
    .Call('mcemGLM_ldmn', PACKAGE = 'mcemGLM', x, sigma)
}

ldmt <- function(x, df, sigma, sigmaType) {
    .Call('mcemGLM_ldmt', PACKAGE = 'mcemGLM', x, df, sigma, sigmaType)
}

MCMCloglikelihoodGammaCpp_n <- function(beta, sigma, alpha, u, kY, kX, kZ) {
    .Call('mcemGLM_MCMCloglikelihoodGammaCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, kY, kX, kZ)
}

MCMCloglikelihoodGammaCpp_t <- function(beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_MCMCloglikelihoodGammaCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

MCMCloglikelihoodLogitCpp_n <- function(beta, sigma, u, kY, kX, kZ) {
    .Call('mcemGLM_MCMCloglikelihoodLogitCpp_n', PACKAGE = 'mcemGLM', beta, sigma, u, kY, kX, kZ)
}

MCMCloglikelihoodLogitCpp_t <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_MCMCloglikelihoodLogitCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

MCMCloglikelihoodNegBinomCpp_n <- function(beta, sigma, alpha, u, kY, kX, kZ) {
    .Call('mcemGLM_MCMCloglikelihoodNegBinomCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, kY, kX, kZ)
}

MCMCloglikelihoodNegBinomCpp_t <- function(beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_MCMCloglikelihoodNegBinomCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

MCMCloglikelihoodPoissonCpp_n <- function(beta, sigma, u, kY, kX, kZ) {
    .Call('mcemGLM_MCMCloglikelihoodPoissonCpp_n', PACKAGE = 'mcemGLM', beta, sigma, u, kY, kX, kZ)
}

MCMCloglikelihoodPoissonCpp_t <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_MCMCloglikelihoodPoissonCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

qFunctionCpp_t <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

qFunctionDiagGammaCpp_n <- function(beta, sigma, alpha, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionDiagGammaCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, kKi, u, kY, kX, kZ)
}

qFunctionDiagGammaCpp_t <- function(beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionDiagGammaCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

qFunctionDiagCpp_n <- function(beta, sigma, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionDiagCpp_n', PACKAGE = 'mcemGLM', beta, sigma, kKi, u, kY, kX, kZ)
}

qFunctionDiagNegBinomCpp_n <- function(beta, sigma, alpha, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionDiagNegBinomCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, kKi, u, kY, kX, kZ)
}

qFunctionDiagNegBinomCpp_t <- function(beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionDiagNegBinomCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

qFunctionDiagPoissonCpp_n <- function(beta, sigma, kKi, u, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionDiagPoissonCpp_n', PACKAGE = 'mcemGLM', beta, sigma, kKi, u, kY, kX, kZ)
}

qFunctionDiagPoissonCpp_t <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionDiagPoissonCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

qFunctionDiagCpp_t <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionDiagCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ)
}

qFunctionCpp_n <- function(beta, sigma, sigmaType, u, kY, kX, kZ) {
    .Call('mcemGLM_qFunctionCpp_n', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, kY, kX, kZ)
}

uSamplerCpp <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_uSamplerCpp', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0)
}

uSamplerGammaCpp_n <- function(beta, sigma, alpha, u, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_uSamplerGammaCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, kY, kX, kZ, B, sd0)
}

uSamplerGammaCpp_t <- function(beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_uSamplerGammaCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0)
}

uSamplerCpp_n <- function(beta, sigma, u, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_uSamplerCpp_n', PACKAGE = 'mcemGLM', beta, sigma, u, kY, kX, kZ, B, sd0)
}

uSamplerNegBinomCpp_n <- function(beta, sigma, alpha, u, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_uSamplerNegBinomCpp_n', PACKAGE = 'mcemGLM', beta, sigma, alpha, u, kY, kX, kZ, B, sd0)
}

uSamplerNegBinomCpp_t <- function(beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_uSamplerNegBinomCpp_t', PACKAGE = 'mcemGLM', beta, sigma, alpha, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0)
}

uSamplerPoissonCpp_n <- function(beta, sigma, u, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_uSamplerPoissonCpp_n', PACKAGE = 'mcemGLM', beta, sigma, u, kY, kX, kZ, B, sd0)
}

uSamplerPoissonCpp_t <- function(beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0) {
    .Call('mcemGLM_uSamplerPoissonCpp_t', PACKAGE = 'mcemGLM', beta, sigma, sigmaType, u, df, kKi, kLh, kLhi, kY, kX, kZ, B, sd0)
}