R/RcppExports.R

In scristia/CNPBayes: Bayesian mixture models for copy number polymorphisms

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

getK <- function(hyperparams) {
    .Call('_CNPBayes_getK', PACKAGE = 'CNPBayes', hyperparams)
}

getDf <- function(hyperparams) {
    .Call('_CNPBayes_getDf', PACKAGE = 'CNPBayes', hyperparams)
}

unique_batch <- function(x) {
    .Call('_CNPBayes_unique_batch', PACKAGE = 'CNPBayes', x)
}

tableZ <- function(K, z) {
    .Call('_CNPBayes_tableZ', PACKAGE = 'CNPBayes', K, z)
}

tableBatchZ <- function(xmod) {
    .Call('_CNPBayes_tableBatchZ', PACKAGE = 'CNPBayes', xmod)
}

rMultinom <- function(probs, m) {
    .Call('_CNPBayes_rMultinom', PACKAGE = 'CNPBayes', probs, m)
}

dlocScale_t <- function(x, df, mu, sigma) {
    .Call('_CNPBayes_dlocScale_t', PACKAGE = 'CNPBayes', x, df, mu, sigma)
}

rlocScale_t <- function(n, mu, sigma, df, u) {
    .Call('_CNPBayes_rlocScale_t', PACKAGE = 'CNPBayes', n, mu, sigma, df, u)
}

compute_u_sums <- function(xmod) {
    .Call('_CNPBayes_compute_u_sums', PACKAGE = 'CNPBayes', xmod)
}

compute_heavy_sums <- function(object) {
    .Call('_CNPBayes_compute_heavy_sums', PACKAGE = 'CNPBayes', object)
}

compute_heavy_means <- function(xmod) {
    .Call('_CNPBayes_compute_heavy_means', PACKAGE = 'CNPBayes', xmod)
}

compute_u_sums_batch <- function(xmod) {
    .Call('_CNPBayes_compute_u_sums_batch', PACKAGE = 'CNPBayes', xmod)
}

compute_heavy_sums_batch <- function(object) {
    .Call('_CNPBayes_compute_heavy_sums_batch', PACKAGE = 'CNPBayes', object)
}

compute_heavy_means_batch <- function(xmod) {
    .Call('_CNPBayes_compute_heavy_means_batch', PACKAGE = 'CNPBayes', xmod)
}

log_ddirichlet_ <- function(x_, alpha_) {
    .Call('_CNPBayes_log_ddirichlet_', PACKAGE = 'CNPBayes', x_, alpha_)
}

sample_components <- function(x, size, prob) {
    .Call('_CNPBayes_sample_components', PACKAGE = 'CNPBayes', x, size, prob)
}

compute_loglik <- function(xmod) {
    .Call('_CNPBayes_compute_loglik', PACKAGE = 'CNPBayes', xmod)
}

update_mu <- function(xmod) {
    .Call('_CNPBayes_update_mu', PACKAGE = 'CNPBayes', xmod)
}

update_tau2 <- function(xmod) {
    .Call('_CNPBayes_update_tau2', PACKAGE = 'CNPBayes', xmod)
}

update_sigma20 <- function(xmod) {
    .Call('_CNPBayes_update_sigma20', PACKAGE = 'CNPBayes', xmod)
}

update_nu0 <- function(xmod) {
    .Call('_CNPBayes_update_nu0', PACKAGE = 'CNPBayes', xmod)
}

update_multinomialPr <- function(xmod) {
    .Call('_CNPBayes_update_multinomialPr', PACKAGE = 'CNPBayes', xmod)
}

update_p <- function(xmod) {
    .Call('_CNPBayes_update_p', PACKAGE = 'CNPBayes', xmod)
}

update_weightedp <- function(xmod) {
    .Call('_CNPBayes_update_weightedp', PACKAGE = 'CNPBayes', xmod)
}

update_z <- function(xmod) {
    .Call('_CNPBayes_update_z', PACKAGE = 'CNPBayes', xmod)
}

update_z2 <- function(p_) {
    .Call('_CNPBayes_update_z2', PACKAGE = 'CNPBayes', p_)
}

compute_means <- function(xmod) {
    .Call('_CNPBayes_compute_means', PACKAGE = 'CNPBayes', xmod)
}

compute_vars <- function(xmod) {
    .Call('_CNPBayes_compute_vars', PACKAGE = 'CNPBayes', xmod)
}

compute_prec <- function(xmod) {
    .Call('_CNPBayes_compute_prec', PACKAGE = 'CNPBayes', xmod)
}

compute_logprior <- function(xmod) {
    .Call('_CNPBayes_compute_logprior', PACKAGE = 'CNPBayes', xmod)
}

stageTwoLogLikBatch <- function(xmod) {
    .Call('_CNPBayes_stageTwoLogLikBatch', PACKAGE = 'CNPBayes', xmod)
}

update_theta <- function(xmod) {
    .Call('_CNPBayes_update_theta', PACKAGE = 'CNPBayes', xmod)
}

update_sigma2 <- function(xmod) {
    .Call('_CNPBayes_update_sigma2', PACKAGE = 'CNPBayes', xmod)
}

update_predictive <- function(xmod) {
    .Call('_CNPBayes_update_predictive', PACKAGE = 'CNPBayes', xmod)
}

update_probz <- function(xmod) {
    .Call('_CNPBayes_update_probz', PACKAGE = 'CNPBayes', xmod)
}

cpp_burnin <- function(object) {
    .Call('_CNPBayes_cpp_burnin', PACKAGE = 'CNPBayes', object)
}

cpp_mcmc <- function(object) {
    .Call('_CNPBayes_cpp_mcmc', PACKAGE = 'CNPBayes', object)
}

mb_homozygous_burnin <- function(object) {
    .Call('_CNPBayes_mb_homozygous_burnin', PACKAGE = 'CNPBayes', object)
}

mb_homozygous_mcmc <- function(object) {
    .Call('_CNPBayes_mb_homozygous_mcmc', PACKAGE = 'CNPBayes', object)
}

sample_componentsP <- function(x, size, prob) {
    .Call('_CNPBayes_sample_componentsP', PACKAGE = 'CNPBayes', x, size, prob)
}

update_predictiveP <- function(xmod) {
    .Call('_CNPBayes_update_predictiveP', PACKAGE = 'CNPBayes', xmod)
}

loglik_multibatch_pvar <- function(xmod) {
    .Call('_CNPBayes_loglik_multibatch_pvar', PACKAGE = 'CNPBayes', xmod)
}

sigma20_multibatch_pvar <- function(xmod) {
    .Call('_CNPBayes_sigma20_multibatch_pvar', PACKAGE = 'CNPBayes', xmod)
}

nu0_multibatch_pvar <- function(xmod) {
    .Call('_CNPBayes_nu0_multibatch_pvar', PACKAGE = 'CNPBayes', xmod)
}

multinomialPr_multibatch_pvar <- function(xmod) {
    .Call('_CNPBayes_multinomialPr_multibatch_pvar', PACKAGE = 'CNPBayes', xmod)
}

z_multibatch_pvar <- function(xmod) {
    .Call('_CNPBayes_z_multibatch_pvar', PACKAGE = 'CNPBayes', xmod)
}

stagetwo_multibatch_pvar <- function(xmod) {
    .Call('_CNPBayes_stagetwo_multibatch_pvar', PACKAGE = 'CNPBayes', xmod)
}

theta_multibatch_pvar <- function(xmod) {
    .Call('_CNPBayes_theta_multibatch_pvar', PACKAGE = 'CNPBayes', xmod)
}

sigma2_multibatch_pvar <- function(xmod) {
    .Call('_CNPBayes_sigma2_multibatch_pvar', PACKAGE = 'CNPBayes', xmod)
}

burnin_multibatch_pvar <- function(object, mcmcp) {
    .Call('_CNPBayes_burnin_multibatch_pvar', PACKAGE = 'CNPBayes', object, mcmcp)
}

mcmc_multibatch_pvar <- function(object, mcmcp) {
    .Call('_CNPBayes_mcmc_multibatch_pvar', PACKAGE = 'CNPBayes', object, mcmcp)
}

mbp_homozygous_burnin <- function(object) {
    .Call('_CNPBayes_mbp_homozygous_burnin', PACKAGE = 'CNPBayes', object)
}

mbp_homozygous_mcmc <- function(object) {
    .Call('_CNPBayes_mbp_homozygous_mcmc', PACKAGE = 'CNPBayes', object)
}

log_prob_theta <- function(xmod, thetastar) {
    .Call('_CNPBayes_log_prob_theta', PACKAGE = 'CNPBayes', xmod, thetastar)
}

marginal_theta_batch <- function(xmod) {
    .Call('_CNPBayes_marginal_theta_batch', PACKAGE = 'CNPBayes', xmod)
}

log_prob_sigma2 <- function(model, sigma2star) {
    .Call('_CNPBayes_log_prob_sigma2', PACKAGE = 'CNPBayes', model, sigma2star)
}

reduced_sigma_batch <- function(xmod) {
    .Call('_CNPBayes_reduced_sigma_batch', PACKAGE = 'CNPBayes', xmod)
}

log_prob_pmix <- function(xmod, pstar) {
    .Call('_CNPBayes_log_prob_pmix', PACKAGE = 'CNPBayes', xmod, pstar)
}

log_prob_pmix2 <- function(xmod, pstar) {
    .Call('_CNPBayes_log_prob_pmix2', PACKAGE = 'CNPBayes', xmod, pstar)
}

reduced_pi_batch2 <- function(xmod) {
    .Call('_CNPBayes_reduced_pi_batch2', PACKAGE = 'CNPBayes', xmod)
}

log_prob_mu <- function(xmod, mustar) {
    .Call('_CNPBayes_log_prob_mu', PACKAGE = 'CNPBayes', xmod, mustar)
}

reduced_mu_batch <- function(xmod) {
    .Call('_CNPBayes_reduced_mu_batch', PACKAGE = 'CNPBayes', xmod)
}

log_prob_tau2 <- function(xmod) {
    .Call('_CNPBayes_log_prob_tau2', PACKAGE = 'CNPBayes', xmod)
}

reduced_tau_batch <- function(xmod) {
    .Call('_CNPBayes_reduced_tau_batch', PACKAGE = 'CNPBayes', xmod)
}

log_prob_nu0 <- function(xmod, nu0star) {
    .Call('_CNPBayes_log_prob_nu0', PACKAGE = 'CNPBayes', xmod, nu0star)
}

reduced_nu0_batch <- function(xmod) {
    .Call('_CNPBayes_reduced_nu0_batch', PACKAGE = 'CNPBayes', xmod)
}

log_prob_s20 <- function(xmod) {
    .Call('_CNPBayes_log_prob_s20', PACKAGE = 'CNPBayes', xmod)
}

reduced_s20_batch <- function(xmod) {
    .Call('_CNPBayes_reduced_s20_batch', PACKAGE = 'CNPBayes', xmod)
}

log_prob_thetap <- function(xmod, thetastar) {
    .Call('_CNPBayes_log_prob_thetap', PACKAGE = 'CNPBayes', xmod, thetastar)
}

marginal_theta_pooled <- function(xmod) {
    .Call('_CNPBayes_marginal_theta_pooled', PACKAGE = 'CNPBayes', xmod)
}

log_prob_sigmap <- function(xmod, sigma2star) {
    .Call('_CNPBayes_log_prob_sigmap', PACKAGE = 'CNPBayes', xmod, sigma2star)
}

reduced_sigma_pooled <- function(xmod) {
    .Call('_CNPBayes_reduced_sigma_pooled', PACKAGE = 'CNPBayes', xmod)
}

reduced_pi_pooled <- function(xmod) {
    .Call('_CNPBayes_reduced_pi_pooled', PACKAGE = 'CNPBayes', xmod)
}

reduced_pi_pooled2 <- function(xmod) {
    .Call('_CNPBayes_reduced_pi_pooled2', PACKAGE = 'CNPBayes', xmod)
}

reduced_mu_pooled <- function(xmod) {
    .Call('_CNPBayes_reduced_mu_pooled', PACKAGE = 'CNPBayes', xmod)
}

reduced_tau2_pooled <- function(xmod) {
    .Call('_CNPBayes_reduced_tau2_pooled', PACKAGE = 'CNPBayes', xmod)
}

log_prob_nu0p <- function(xmod, nu0star) {
    .Call('_CNPBayes_log_prob_nu0p', PACKAGE = 'CNPBayes', xmod, nu0star)
}

reduced_nu0_pooled <- function(xmod) {
    .Call('_CNPBayes_reduced_nu0_pooled', PACKAGE = 'CNPBayes', xmod)
}

log_prob_s20p <- function(xmod) {
    .Call('_CNPBayes_log_prob_s20p', PACKAGE = 'CNPBayes', xmod)
}

family_member <- function(object) {
    .Call('_CNPBayes_family_member', PACKAGE = 'CNPBayes', object)
}

lookup_mprobs <- function(model, father, mother) {
    .Call('_CNPBayes_lookup_mprobs', PACKAGE = 'CNPBayes', model, father, mother)
}

update_trioPr <- function(xmod) {
    .Call('_CNPBayes_update_trioPr', PACKAGE = 'CNPBayes', xmod)
}

is_father <- function(xmod) {
    .Call('_CNPBayes_is_father', PACKAGE = 'CNPBayes', xmod)
}

is_mother <- function(xmod) {
    .Call('_CNPBayes_is_mother', PACKAGE = 'CNPBayes', xmod)
}

is_parent <- function(xmod) {
    .Call('_CNPBayes_is_parent', PACKAGE = 'CNPBayes', xmod)
}

is_child <- function(xmod) {
    .Call('_CNPBayes_is_child', PACKAGE = 'CNPBayes', xmod)
}

update_trioPr2 <- function(xmod) {
    .Call('_CNPBayes_update_trioPr2', PACKAGE = 'CNPBayes', xmod)
}

prob_mendelian <- function(xmod) {
    .Call('_CNPBayes_prob_mendelian', PACKAGE = 'CNPBayes', xmod)
}

update_mendel_prob <- function(xmod) {
    .Call('_CNPBayes_update_mendel_prob', PACKAGE = 'CNPBayes', xmod)
}

update_mendelian <- function(xmod) {
    .Call('_CNPBayes_update_mendelian', PACKAGE = 'CNPBayes', xmod)
}

update_multinomialPrPar <- function(xmod) {
    .Call('_CNPBayes_update_multinomialPrPar', PACKAGE = 'CNPBayes', xmod)
}

update_parents <- function(xmod) {
    .Call('_CNPBayes_update_parents', PACKAGE = 'CNPBayes', xmod)
}

update_zparents <- function(xmod) {
    .Call('_CNPBayes_update_zparents', PACKAGE = 'CNPBayes', xmod)
}

tableZpar <- function(xmod) {
    .Call('_CNPBayes_tableZpar', PACKAGE = 'CNPBayes', xmod)
}

tableBatchZpar <- function(xmod) {
    .Call('_CNPBayes_tableBatchZpar', PACKAGE = 'CNPBayes', xmod)
}

update_pp <- function(xmod) {
    .Call('_CNPBayes_update_pp', PACKAGE = 'CNPBayes', xmod)
}

update_multinomialPrChild <- function(xmod) {
    .Call('_CNPBayes_update_multinomialPrChild', PACKAGE = 'CNPBayes', xmod)
}

update_offspring <- function(xmod) {
    .Call('_CNPBayes_update_offspring', PACKAGE = 'CNPBayes', xmod)
}

update_zchild <- function(xmod) {
    .Call('_CNPBayes_update_zchild', PACKAGE = 'CNPBayes', xmod)
}

update_mu2 <- function(xmod) {
    .Call('_CNPBayes_update_mu2', PACKAGE = 'CNPBayes', xmod)
}

compute_vars2 <- function(xmod) {
    .Call('_CNPBayes_compute_vars2', PACKAGE = 'CNPBayes', xmod)
}

compute_prec2 <- function(xmod) {
    .Call('_CNPBayes_compute_prec2', PACKAGE = 'CNPBayes', xmod)
}

update_probzpar <- function(xmod) {
    .Call('_CNPBayes_update_probzpar', PACKAGE = 'CNPBayes', xmod)
}

update_sigma22 <- function(xmod) {
    .Call('_CNPBayes_update_sigma22', PACKAGE = 'CNPBayes', xmod)
}

sample_trio_components <- function(x, size, prob) {
    .Call('_CNPBayes_sample_trio_components', PACKAGE = 'CNPBayes', x, size, prob)
}

predictive_trios <- function(xmod) {
    .Call('_CNPBayes_predictive_trios', PACKAGE = 'CNPBayes', xmod)
}

trios_burnin <- function(object) {
    .Call('_CNPBayes_trios_burnin', PACKAGE = 'CNPBayes', object)
}

test_trio <- function(object) {
    .Call('_CNPBayes_test_trio', PACKAGE = 'CNPBayes', object)
}

trios_mcmc <- function(object) {
    .Call('_CNPBayes_trios_mcmc', PACKAGE = 'CNPBayes', object)
}

z2cn <- function(xmod, map) {
    .Call('_CNPBayes_z2cn', PACKAGE = 'CNPBayes', xmod, map)
}

burnin_nomendelian_update <- function(object) {
    .Call('_CNPBayes_burnin_nomendelian_update', PACKAGE = 'CNPBayes', object)
}

mcmc_nomendelian_update <- function(object) {
    .Call('_CNPBayes_mcmc_nomendelian_update', PACKAGE = 'CNPBayes', object)
}