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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.
# One hundred days model
# Each manifest represents a single variable as measured on a different day, days 1-100
# Three predicting latents. Over the trial, one represents a constant part,
# one represents a linear part, and one an exponential part
require(OpenMx)
# Random covariance matrix
manifests <- unlist(lapply(1:100, function(n) { paste("Day",n, sep="") } ))
latents <- c('Const', 'Lin', 'Exp')
amtT <- 100
amtStep <- amtT / 99
ConstLoadings <- rep(1,100)
LinLoadings <- unlist(lapply(1:100, function (n) { n*amtStep/(amtT-1) } ))
EXPFACTOR <- 0.22
ExpLoadings <- unlist(lapply(1:100, function (n) { -exp(-EXPFACTOR*n*amtStep) } ))
lambda <- cbind(ConstLoadings, LinLoadings, ExpLoadings)
dataLatents <- matrix(rnorm(3*3), 3, 3)
dataTest <- lambda %*% dataLatents %*% t(dataLatents) %*% t(lambda) + diag(rep(1,100))
dataTest <- (dataTest + t(dataTest)) / 2
dataRaw <- mvtnorm::rmvnorm(n=5000, rep(0,100), dataTest)
colnames(dataRaw) <- manifests
colnames(dataTest) <- manifests
rownames(dataTest) <- manifests
factorModel <- mxModel("One Hundred Days Model",
type="RAM",
# Vars
manifestVars = manifests,
latentVars = latents,
# A
mxPath(from='Const', to=manifests,value=ConstLoadings, free=FALSE),
mxPath(from='Lin', to=manifests,value=LinLoadings, free=FALSE),
mxPath(from='Exp', to=manifests,value=ExpLoadings, free=FALSE),
# S
mxPath(from=manifests, arrows=2,value=rep(1.0, 100), labels=rep("Res", 100)),
#mxPath(from=latents, arrows=2,values=1.0),
mxPath(from="Const", to=latents, arrows=2,values=1.0),
mxPath(from="Lin", to=latents, arrows=2,values=1.0),
mxPath(from="Exp", to=latents, arrows=2,values=1.0),
# Means
mxPath(from="one", to=latents, values=0, free=TRUE),
# Data
mxData(dataRaw, type="raw", numObs=5000)
)
factorModelOut <- mxRun(imxPPML(factorModel, FALSE))
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