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#
# Copyright 2007-2018 by the individuals mentioned in the source code history
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# -----------------------------------------------------------------------------
# Program: OneFactorMatrixDemo.R
# Author: Steve Boker
# Date: 2009.08.01
#
# ModelType: Factor
# DataType: Continuous
# Field: None
#
# Purpose:
# OpenMx one factor matrix model demo from front page of website
#
# RevisionHistory:
# Hermine Maes -- 2009.10.08 updated & reformatted
# Ross Gore -- 2011.06.06 added Model, Data & Field metadata
# Mike Hunter -- 2013.09.16 Identified model by fixing variance to 1.0
# Tim Bates -- 2014.10.12 reformatted
# -----------------------------------------------------------------------------
require(OpenMx)
# Load Library
# -----------------------------------------------------------------------------
data(demoOneFactor)
# Prepare Data
# -----------------------------------------------------------------------------
factorModel <- mxModel(name ="One Factor",
mxMatrix(type="Full", nrow=5, ncol=1, free=TRUE, values=0.2, name="A"),
mxMatrix(type="Symm", nrow=1, ncol=1, free=FALSE, values=1, name="L"),
mxMatrix(type="Diag", nrow=5, ncol=5, free=TRUE, values=1, name="U"),
mxAlgebra(expression=A %*% L %*% t(A) + U, name="R"),
mxFitFunctionML(),mxExpectationNormal(covariance="R", dimnames=names(demoOneFactor)),
mxData(observed=cov(demoOneFactor), type="cov", numObs=500)
)
# Create an MxModel object
# -----------------------------------------------------------------------------
factorFit <- mxRun(factorModel)
# Fit the model to the observed covariances with mxRun
# -----------------------------------------------------------------------------
summary(factorFit)
# Print a summary of the results
# -----------------------------------------------------------------------------
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