% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/SVD_MM.R
\name{sdv_MM}
\alias{sdv_MM}
\title{Fit a Binary Logistic Biplot via Coordinate Descent MM Algorithm}
\usage{
sdv_MM(
  x,
  k = 5,
  iterations = 1000,
  truncated = TRUE,
  random = FALSE,
  epsilon = 1e-04
)
}
\arguments{
\item{x}{A binary matrix with no missing values.}

\item{k}{Number of dimensions. Default is \code{k = 5}.}

\item{iterations}{Maximum number of iterations. Default is \code{1000}.}

\item{truncated}{Logical; if \code{TRUE} (default for large matrices), the
truncated SVD from \pkg{RSpectra} is used to speed up computation.}

\item{random}{Logical; if \code{TRUE}, parameters are initialised randomly.
Default is \code{FALSE} (SVD initialisation).}

\item{epsilon}{Convergence tolerance. The algorithm stops when the relative
decrease in the loss function is below this value. Default is \code{1e-4}.}
}
\value{
A named list with components:
  \describe{
    \item{\code{mu}}{Estimated intercept vector of length \eqn{p}.}
    \item{\code{A}}{Estimated row-marker matrix (\eqn{n \times k}).}
    \item{\code{B}}{Estimated column-marker matrix (\eqn{p \times k}).}
    \item{\code{iterations}}{Number of iterations performed.}
    \item{\code{loss_func}}{Vector of normalised loss-function values at each
      iteration.}
  }
}
\description{
Estimates the intercept vector \eqn{\mu}, the row-marker matrix \strong{A},
and the column-marker matrix \strong{B} using an iterative coordinate descent
Majorization-Minimization (MM) algorithm. This is the low-level function
called by \code{\link{LogBip}} when \code{method = "MM"}.
}
\examples{
\donttest{
data("Methylation")
out <- sdv_MM(x = Methylation)
}
}
\references{
Babativa-Marquez, J. G., & Vicente-Villardon, J. L. (2021). Logistic biplot
by conjugate gradient algorithms and iterated SVD. \emph{Mathematics},
\emph{9}(16), 2015. \doi{10.3390/math9162015}

Vicente-Villardon, J. L., & Galindo, M. P. (2006). Logistic biplots. In
M. Greenacre & J. Blasius (Eds.), \emph{Multiple Correspondence Analysis and
Related Methods} (pp. 503--521). Chapman & Hall.
}
\seealso{
\code{\link{LogBip}}, \code{\link{cv_LogBip}}
}
\author{
Giovany Babativa <jgbabativam@unal.edu.co>
}
