% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/nmfkc.net.R
\name{nmfkc.net.inference}
\alias{nmfkc.net.inference}
\title{Statistical Inference for Symmetric NMF Parameters}
\usage{
nmfkc.net.inference(object, Y, wild.bootstrap = TRUE, ...)
}
\arguments{
\item{object}{A fitted model returned by \code{nmfkc()} with
\code{Y.symmetric = "bi"} or \code{"tri"}, or the newer
\code{\link{nmfkc.net}} with \code{type = "bi"} or \code{"tri"}.}

\item{Y}{The original symmetric matrix (P x P).}

\item{wild.bootstrap}{Logical; if TRUE (default), perform wild bootstrap
inference for the C matrix.}

\item{...}{Additional arguments passed to \code{nmfkc.inference()}
(e.g., \code{wild.B}, \code{wild.seed}, \code{C.p.side}).}
}
\value{
The object augmented with inference fields
(same as \code{nmfkc.inference}), with class
\code{c("nmfkc.net.inference", "nmfkc.inference", "nmf.inference", "nmfkc", "nmf")}.
}
\description{
Performs statistical inference on the parameter matrix \eqn{C} of a
symmetric NMF model (\eqn{Y \approx XCX^\top}).

This is a wrapper around \code{\link{nmfkc.inference}} that automatically
sets the covariate matrix to \eqn{A = X^\top}, which is the defining
property of symmetric NMF.
}
\section{Lifecycle}{

This function is \strong{experimental}. The interface may change in
future versions; details are to be described in an upcoming paper.
}

\examples{
\donttest{
library(nmfkc)
Y <- matrix(c(0,1,1,0,0,0,
              1,0,1,0,0,0,
              1,1,0,1,0,0,
              0,0,1,0,1,1,
              0,0,0,1,0,1,
              0,0,0,1,1,0), 6, 6)
res <- nmfkc.net(Y, rank = 2, type = "tri", nstart = 20)
res_inf <- nmfkc.net.inference(res, Y)
summary(res_inf)
}

}
\seealso{
\code{\link{nmfkc.inference}}, \code{\link{nmfkc.net.DOT}},
\code{\link{summary.nmfkc.net.inference}}
}
