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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.
require(OpenMx)
myDataRaw<-read.table("data/myAutoregressiveData.txt",header=T)
myDataCov<-matrix(
c(0.672, 0.315, 0.097, -0.037, 0.046,
0.315, 1.300, 0.428, 0.227, 0.146,
0.097, 0.428, 1.177, 0.568, 0.429,
-0.037, 0.227, 0.568, 1.069, 0.468,
0.046, 0.146, 0.429, 0.468, 1.031),
nrow=5,
dimnames=list(
c("x1","x2","x3","x4","x5"),
c("x1","x2","x3","x4","x5"))
)
myDataMeans <- c(3.054, 1.385, 0.680, 0.254, -0.027)
names(myDataMeans) <- c("x1","x2","x3","x4","x5")
model<-mxModel("Autoregressive Model Path",
type="RAM",
mxData(myDataCov,type="cov", means=myDataMeans, numObs=100),
manifestVars=c("x1","x2","x3","x4","x5"),
mxPath(from=c("x1","x2","x3","x4"),
to=c("x2","x3","x4","x5"),
arrows=1,
free=TRUE,
values=c(1,1,1,1),
labels=c("beta","beta","beta","beta")
),
mxPath(from=c("x1","x2","x3","x4","x5"),
arrows=2,
free=TRUE,
values=c(1,1,1,1,1),
labels=c("varx1","e2","e3","e4","e5")
),
mxPath(from="one",
to=c("x1","x2","x3","x4","x5"),
arrows=1,
free=TRUE,
values=c(1,1,1,1,1),
labels=c("mean1","mean2","mean3","mean4","mean5")
)
) # close model
autoregressivePathCov<-mxRun(model)
autoregressivePathCov$output
# Slightly disagrees with old Mx Output, but matches Mplus exactly
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["beta"]], 0.427, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["varx1"]], 0.665, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["e2"]], 1.142, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["e3"]], 1.038, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["e4"]], 0.791, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["e5"]], 0.818, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["mean1"]], 3.054, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["mean2"]], 0.082, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["mean3"]], 0.089, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["mean4"]], -0.036, 0.001)
omxCheckCloseEnough(autoregressivePathCov$output$estimate[["mean5"]], -0.135, 0.001)
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