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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)
fix_matrix <- function(m)
{
for (i in 1:dim(m$labels)[1])
{
for (j in 1:dim(m$labels)[2])
{
m$free[i,j] <- FALSE;
}
}
return(m);
}
# (2)
# generate random normal data Y~N(0,1)
#
N <- 1000
Y <- rnorm(N,0,1)
data <- data.frame(Y)
names(data) <- c("Y")
# (3)
# create a dummy model which estimates the mean
# of an observed variable with unit variance
#
model <- mxModel("One Factor", type="RAM",
manifestVars = c("Y"),
latentVars = c(),
mxPath(from=c("Y"), arrows=2,
free=F, values=1.0, label=c("lat_var")),
mxPath(
from="one",
to=c("Y"),
arrows=1,
free=TRUE,
values=c(1),
labels=c("mean")
) ,
mxData( data, type="raw", numObs=dim(data)[1])
);
# (4)
# run model (with a single free param)
# and estimate mean
#
run <- mxRun(model);
#################
# rewrite version
#################
m <- run$A$values[1,1]
test <- mxModel("test",
mxData(data, "raw"),
mxMatrix("Symm", 1, 1, FALSE, 1, name="S"),
mxMatrix("Full", 1, 1, name="A"),
mxMatrix("Iden", 1, name="F"),
mxMatrix("Full", 1, 1, FALSE, m, name="M"),
mxFitFunctionML(),mxExpectationRAM("A", "S", "F", "M", dimnames=c("Y"))
)
# runs fine
test2 <- mxRun(test)
# flipping parameters
test3 <- run
test3$M$free[1,1] <- F
test4 <- mxRun(test3)
# test3$output <- list()
test5 <- mxRun(test3)
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