R/RcppExports.R

In manuelreif/PP: Person Parameter Estimation

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

P_4pl <- function(delta, alpha, theta, la, ua) {
    .Call(`_PP_P_4pl`, delta, alpha, theta, la, ua)
}

P_4pl4wle <- function(delta, alpha, theta, la, ua) {
    .Call(`_PP_P_4pl4wle`, delta, alpha, theta, la, ua)
}

r_huber_4pl <- function(delta, alpha, theta, la, ua, H) {
    .Call(`_PP_r_huber_4pl`, delta, alpha, theta, la, ua, H)
}

L4pl <- function(awm, DELTA, ALPHA, LOWA, UPPA, THETA, map, mu, sigma2) {
    .Call(`_PP_L4pl`, awm, DELTA, ALPHA, LOWA, UPPA, THETA, map, mu, sigma2)
}

L4pl_wle <- function(awm, DELTA, ALPHA, LOWA, UPPA, THETA) {
    .Call(`_PP_L4pl_wle`, awm, DELTA, ALPHA, LOWA, UPPA, THETA)
}

L4pl_robust <- function(awm, DELTA, ALPHA, LOWA, UPPA, THETA, H) {
    .Call(`_PP_L4pl_robust`, awm, DELTA, ALPHA, LOWA, UPPA, THETA, H)
}

NR_4PL <- function(awm, DELTA, ALPHA, LOWA, UPPA, THETA, wm, maxsteps, exac, mu, sigma2, H) {
    .Call(`_PP_NR_4PL`, awm, DELTA, ALPHA, LOWA, UPPA, THETA, wm, maxsteps, exac, mu, sigma2, H)
}

P_gpcm <- function(delta, alpha, theta, resp) {
    .Call(`_PP_P_gpcm`, delta, alpha, theta, resp)
}

r_huber_gpcm <- function(delta, alpha, theta, H) {
    .Call(`_PP_r_huber_gpcm`, delta, alpha, theta, H)
}

L12gpcm <- function(awm, DELTA, ALPHA, THETA, mu, sigma2, map) {
    .Call(`_PP_L12gpcm`, awm, DELTA, ALPHA, THETA, mu, sigma2, map)
}

Pcorr1_gpcm <- function(delta, alpha, theta) {
    .Call(`_PP_Pcorr1_gpcm`, delta, alpha, theta)
}

L12gpcm_wle <- function(awm, DELTA, ALPHA, THETA) {
    .Call(`_PP_L12gpcm_wle`, awm, DELTA, ALPHA, THETA)
}

L12gpcm_robust <- function(awm, DELTA, ALPHA, THETA, H) {
    .Call(`_PP_L12gpcm_robust`, awm, DELTA, ALPHA, THETA, H)
}

NR_GPCM <- function(awm, DELTA, ALPHA, THETA, wm, maxsteps, exac, mu, sigma2, H) {
    .Call(`_PP_NR_GPCM`, awm, DELTA, ALPHA, THETA, wm, maxsteps, exac, mu, sigma2, H)
}

Lgpcm4pl_mle <- function(awm, DELTA, ALPHA, LOWA, UPPA, THETA, model, mu, sigma2, map) {
    .Call(`_PP_Lgpcm4pl_mle`, awm, DELTA, ALPHA, LOWA, UPPA, THETA, model, mu, sigma2, map)
}

Lgpcm4pl_wle <- function(awm, DELTA, ALPHA, LOWA, UPPA, THETA, model) {
    .Call(`_PP_Lgpcm4pl_wle`, awm, DELTA, ALPHA, LOWA, UPPA, THETA, model)
}

Lgpcm4pl_robust <- function(awm, DELTA, ALPHA, LOWA, UPPA, THETA, model, H) {
    .Call(`_PP_Lgpcm4pl_robust`, awm, DELTA, ALPHA, LOWA, UPPA, THETA, model, H)
}

NR_mixed <- function(awm, DELTA, ALPHA, LOWA, UPPA, THETA, model, wm, maxsteps, exac, mu, sigma2, H) {
    .Call(`_PP_NR_mixed`, awm, DELTA, ALPHA, LOWA, UPPA, THETA, model, wm, maxsteps, exac, mu, sigma2, H)
}

Likgpcm <- function(awv, DELTA, ALPHA, nodes) {
    .Call(`_PP_Likgpcm`, awv, DELTA, ALPHA, nodes)
}

#' Simulate data for 1/2/3/4-pl model
#' 
#' This function returns a dichotomous matrix of simulated responses under given item and person parameters.
#' 
#' @useDynLib PP
#' @importFrom Rcpp evalCpp sourceCpp
#' 
#'@param beta A numeric vector which contains the difficulty parameters for each item.
#'@param alpha A numeric vector, which contains the slope parameters for each item.
#'@param lowerA A numeric vector, which contains the lower asymptote parameters (kind of guessing parameter) for each item.
#'@param upperA numeric vector, which contains the upper asymptote parameters for each item.
#'@param theta A numeric vector which contains person parameters.
#'
#'@seealso \link{sim_gpcm}, \link{PP_4pl}
#'@example ./R/.examples_sim.R
#'
#'@author Manuel Reif
#'
#' @export
sim_4pl <- function(beta, alpha, lowerA, upperA, theta) {
    .Call(`_PP_sim_4pl`, beta, alpha, lowerA, upperA, theta)
}

ansol <- function(awm, maxsc) {
    .Call(`_PP_ansol`, awm, maxsc)
}