R/RcppExports.R

Defines functions rSigma Info pAlpha pBeta wls fastInv

Documented in fastInv Info pAlpha pBeta rSigma wls

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

#' Fast Inverse
#' 
#' Matrix pseudo-inverse. 
#' @param A Numeric matrix.
fastInv <- function(A) {
    .Call(`_BinaryModels_fastInv`, A)
}

#' Weight Least Squares Estimator
#' 
#' Estimates the coefficient of a WLS model
#' @param z Outcome
#' @param X Design matrix
#' @param W Weight matrix
#' 
wls <- function(z, X, W) {
    .Call(`_BinaryModels_wls`, z, X, W)
}

#' Probit Estimate Beta
#' 
#' PX-E Estimate of beta
#' @param z1 Expectation of z given y
#' @param X Design matrix
pBeta <- function(z1, X) {
    .Call(`_BinaryModels_pBeta`, z1, X)
}

#' Estimate Alpha
#' 
#' PX-E Estimate of alpha
#' @param z1 Expectation of z given y
#' @param z2 Expectation of \eqn{z^2} given y
#' @param eta Linear predictor
pAlpha <- function(z1, z2, eta) {
    .Call(`_BinaryModels_pAlpha`, z1, z2, eta)
}

#' Probit Information Matrix
#' 
#' Calculate information matrix for probit coefficient
#' @param X Design matrix
#' @param W Weight matrix
Info <- function(X, W) {
    .Call(`_BinaryModels_Info`, X, W)
}

#' Robit Estimate of Sigma
#' 
#' PX-E Estimate of sigma
#' @param nu Degrees of freedom
#' @param z1 Expectation of z given y
#' @param eta Linear predictor
#' @param tau1 Expectation of \eqn{\tau} given y
#' @param X Design matrix
rSigma <- function(nu, z1, eta, T1, X) {
    .Call(`_BinaryModels_rSigma`, nu, z1, eta, T1, X)
}
zrmacc/BinaryModels documentation built on Jan. 14, 2018, 9:09 a.m.