% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/computing_GMM_estimator.R
\name{computing_GMM_estimator}
\alias{computing_GMM_estimator}
\title{GMM estimator combining moment-corrected and phase-function equations}
\usage{
computing_GMM_estimator(
  W,
  y,
  Zmat,
  weight_method = c("uniform", "minimax", "quasi-likelihood"),
  B = 100,
  t_grid_length = 1000
)
}
\arguments{
\item{W}{Numeric array of dimension \code{n x p x J} containing replicate
measurements of contaminated covariates.}

\item{y}{Numeric vector of length \code{n} containing the response.}

\item{Zmat}{Numeric matrix of dimension \code{n x q} containing error-free
covariates.}

\item{B}{Integer specifying the number of bootstrap replicates.}

\item{t_grid_length}{Integer specifying the length of optimal t for
computational intergration.}
}
\value{
A list with components:
\describe{
  \item{est}{Numeric matrix of GMM estimates; one column per weight choice.}
  \item{CV_boot}{Array of bootstrap covariance matrices used in GMM.}
}
}
\description{
Computes Generalized Method of Moments (GMM) estimators by combining
moment-corrected estimating equations and phase-function estimating
equations. The GMM weighting matrix is estimated via a cluster bootstrap
that accounts for uncertainty in estimating the measurement error
covariance.
}
\keyword{internal}
