% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/estpw_d_matrix_alp.R
\name{compute_D_ALP}
\alias{compute_D_ALP}
\title{Compute design-based covariance matrix D for ALP}
\usage{
compute_D_ALP(sp_des, p_sp, Xp)
}
\arguments{
\item{sp_des}{A survey design object of class `"survey.design2"` or
`"svyrep.design"`.}

\item{p_sp}{Numeric vector of estimated participation probabilities
for the probability sample. Length must equal the number of rows in
`sp_des$variables`.}

\item{Xp}{Numeric matrix of dimension `n_p x p`. Each row is the
covariate vector `x_j` used in the ALP estimating equation.}
}
\value{
A `p x p` covariance matrix `D`.
}
\description{
Internal helper to compute
\deqn{D = Var_p\left( \sum_{j \in s_p} d_j p_j x_j \right)}
from an existing survey design object created by
survey::svydesign() or survey::svrepdesign().
}
\details{
In the ALP method, the probability sample contribution in the
estimating equation is \eqn{p_j d_j x_j}, so the design-based
covariance matrix is obtained by treating \eqn{h_j = p_j x_j}
as the survey total variable.
}
\keyword{internal}
