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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/MxCompute.R
\name{mxComputePenaltySearch}
\alias{mxComputePenaltySearch}
\alias{MxComputePenaltySearch-class}
\title{Regularize parameter estimates}
\usage{
mxComputePenaltySearch(
plan,
...,
freeSet = NA_character_,
verbose = 0L,
fitfunction = "fitfunction",
approach = "EBIC",
ebicGamma = 0.5
)
}
\arguments{
\item{plan}{compute plan to optimize the model}
\item{...}{Not used. Forces remaining arguments to be specified by name.}
\item{freeSet}{names of matrices containing free variables}
\item{verbose}{integer. Level of run-time diagnostic output. Set to zero to disable}
\item{fitfunction}{the name of the deviance function}
\item{approach}{what fit function to use to compare regularized models? Currently only EBIC is available}
\item{ebicGamma}{what Gamma value to use for EBIC? Must be between 0 and 1}
}
\description{
Add a penalty to push some subset of the parameter estimates toward zero.
}
\references{
Jacobucci, R., Grimm, K. J., & McArdle, J. J. (2016).
Regularized structural equation modeling.
<i>Structural equation modeling: a multidisciplinary journal, 23</i>(4), 555-566.
}
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