R/RcppExports.R

In nathansam/SMLN: Bayesian Survival Analysis Using Shape Mixtures of Log-Normal Distributions

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

prior_LEP <- function(beta, sigma2, alpha, prior, logs) {
    .Call(`_BASSLINE_prior_LEP`, beta, sigma2, alpha, prior, logs)
}

d_texp <- function(x, trunc) {
    .Call(`_BASSLINE_d_texp`, x, trunc)
}

MH_marginal_sigma2 <- function(omega2, logt, X, beta, alpha, sigma20, prior) {
    .Call(`_BASSLINE_MH_marginal_sigma2`, omega2, logt, X, beta, alpha, sigma20, prior)
}

alpha_beta <- function(beta_0, beta_1, logt, X, sigma2, alpha) {
    .Call(`_BASSLINE_alpha_beta`, beta_0, beta_1, logt, X, sigma2, alpha)
}

alpha_sigma2 <- function(sigma2_0, sigma2_1, logt, X, beta, alpha, prior) {
    .Call(`_BASSLINE_alpha_sigma2`, sigma2_0, sigma2_1, logt, X, beta, alpha, prior)
}

MH_marginal_alpha <- function(omega2, logt, X, beta, sigma2, alpha0, prior) {
    .Call(`_BASSLINE_MH_marginal_alpha`, omega2, logt, X, beta, sigma2, alpha0, prior)
}

MH_marginal_beta_j <- function(omega2, logt, X, sigma2, alpha, beta0, j) {
    .Call(`_BASSLINE_MH_marginal_beta_j`, omega2, logt, X, sigma2, alpha, beta0, j)
}

alpha_alpha <- function(alpha0, alpha1, logt, X, beta, sigma2, prior) {
    .Call(`_BASSLINE_alpha_alpha`, alpha0, alpha1, logt, X, beta, sigma2, prior)
}

d_normp <- function(x, mu, sigmap, p, logs = FALSE) {
    .Call(`_BASSLINE_d_normp`, x, mu, sigmap, p, logs)
}

p_normp <- function(q, mu, sigmap, p, lower_tail = TRUE, log_pr = FALSE) {
    .Call(`_BASSLINE_p_normp`, q, mu, sigmap, p, lower_tail, log_pr)
}

log_lik_LEP <- function(Time, Cens, X, beta, sigma2, alpha, set, eps_l, eps_r) {
    .Call(`_BASSLINE_log_lik_LEP`, Time, Cens, X, beta, sigma2, alpha, set, eps_l, eps_r)
}

Post_u_obs_LEP <- function(obs, ref, X, chain) {
    .Call(`_BASSLINE_Post_u_obs_LEP`, obs, ref, X, chain)
}

r_GIG <- function(r) {
    .Call(`_BASSLINE_r_GIG`, r)
}

RS_lambda_obs_LLOG <- function(logt, X, beta, sigma2, obs, N_AKS) {
    .Call(`_BASSLINE_RS_lambda_obs_LLOG`, logt, X, beta, sigma2, obs, N_AKS)
}

prior_LN <- function(beta, sigma2, prior, logs) {
    .Call(`_BASSLINE_prior_LN`, beta, sigma2, prior, logs)
}

J_alpha <- function(alpha, k) {
    .Call(`_BASSLINE_J_alpha`, alpha, k)
}

J_alpha_single <- function(alpha, k) {
    .Call(`_BASSLINE_J_alpha_single`, alpha, k)
}

II_alpha <- function(alpha) {
    .Call(`_BASSLINE_II_alpha`, alpha)
}

II_alpha_single <- function(alpha) {
    .Call(`_BASSLINE_II_alpha_single`, alpha)
}

I_alpha <- function(alpha) {
    .Call(`_BASSLINE_I_alpha`, alpha)
}

I_alpha_single <- function(alpha) {
    .Call(`_BASSLINE_I_alpha_single`, alpha)
}

prior_alpha <- function(alpha, k, prior) {
    .Call(`_BASSLINE_prior_alpha`, alpha, k, prior)
}

prior_alpha_single <- function(alpha, k, prior) {
    .Call(`_BASSLINE_prior_alpha_single`, alpha, k, prior)
}

rtnorm <- function(n, lower, upper, mu, sd) {
    .Call(`_BASSLINE_rtnorm`, n, lower, upper, mu, sd)
}

mvrnormArma <- function(n, mu, Sigma) {
    .Call(`_BASSLINE_mvrnormArma`, n, mu, Sigma)
}

mvrnormArma2 <- function(n, mu, Sigma) {
    .Call(`_BASSLINE_mvrnormArma2`, n, mu, Sigma)
}

logt_update_SMLN <- function(Time, Cens, X, beta, sigma2, set, eps_l, eps_r) {
    .Call(`_BASSLINE_logt_update_SMLN`, Time, Cens, X, beta, sigma2, set, eps_l, eps_r)
}

MCMC_LN_CPP <- function(N, thin, burn, Time, Cens, X, beta0, sigma20, prior, set, eps_l, eps_r) {
    .Call(`_BASSLINE_MCMC_LN_CPP`, N, thin, burn, Time, Cens, X, beta0, sigma20, prior, set, eps_l, eps_r)
}

prior_nu_single <- function(nu, prior) {
    .Call(`_BASSLINE_prior_nu_single`, nu, prior)
}

prior_LST <- function(beta, sigma2, nu, prior, logs) {
    .Call(`_BASSLINE_prior_LST`, beta, sigma2, nu, prior, logs)
}

alpha_nu <- function(nu0, nu1, lambda, prior) {
    .Call(`_BASSLINE_alpha_nu`, nu0, nu1, lambda, prior)
}

MH_nu_LST <- function(omega2, beta, lambda, nu0, prior) {
    .Call(`_BASSLINE_MH_nu_LST`, omega2, beta, lambda, nu0, prior)
}

log_lik_LST <- function(Time, Cens, X, beta, sigma2, nu, set, eps_l, eps_r) {
    .Call(`_BASSLINE_log_lik_LST`, Time, Cens, X, beta, sigma2, nu, set, eps_l, eps_r)
}

Post_lambda_obs_LST <- function(obs, ref, X, chain) {
    .Call(`_BASSLINE_Post_lambda_obs_LST`, obs, ref, X, chain)
}