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#
# Copyright 2007-2021 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.
setClass(Class = "MxFitFunctionGREML",
slots=c(
dV = "MxCharOrNumber",
dVnames = "character",
MLfit = "numeric",
numObsAdjust = "integer",
aug = "MxCharOrNumber",
augGrad = "MxCharOrNumber",
augHess = "MxCharOrNumber",
autoDerivType = "character",
infoMatType = "character"),
contains = "MxBaseFitFunction")
setMethod("initialize", "MxFitFunctionGREML",
function(.Object, ...) {
.Object <- callNextMethod()
.Object@dV <- ..1
.Object@dVnames <- as.character(names(..1))
.Object@MLfit <- 0
.Object@vector <- FALSE
.Object@numObsAdjust <- 0L
.Object@aug <- ..2
.Object@augGrad <- ..3
.Object@augHess <- ..4
.Object@autoDerivType <- ..5
.Object@infoMatType <- ..6
.Object
})
setMethod("qualifyNames", signature("MxFitFunctionGREML"),
function(.Object, modelname, namespace) {
.Object <- callNextMethod()
if(length(.Object@dV)){
.Object@dV <- sapply(.Object@dV, imxConvertIdentifier, modelname, namespace)
.Object@dVnames <- names(.Object@dV)
}
if(length(.Object@aug)){.Object@aug <- imxConvertIdentifier(.Object@aug[1],modelname,namespace)}
if(length(.Object@augGrad)){
.Object@augGrad <- imxConvertIdentifier(.Object@augGrad[1],modelname,namespace)
}
if(length(.Object@augHess)){
.Object@augHess <- imxConvertIdentifier(.Object@augHess[1],modelname,namespace)
}
return(.Object)
})
setMethod("genericFitRename", signature("MxFitFunctionGREML"),
function(.Object, oldname, newname) {
if(length(.Object@dV)){
.Object@dV <- sapply(.Object@dV, renameReference, oldname, newname)
}
if(length(.Object@aug)){.Object@aug <- renameReference(.Object@aug[1], oldname, newname)}
if(length(.Object@augGrad)){
.Object@augGrad <- renameReference(.Object@augGrad[1], oldname, newname)
}
if(length(.Object@augHess)){
.Object@augHess <- renameReference(.Object@augHess[1], oldname, newname)
}
return(.Object)
})
setMethod("genericFitConvertEntities", "MxFitFunctionGREML",
function(.Object, flatModel, namespace, labelsData) {
name <- .Object@name
modelname <- imxReverseIdentifier(flatModel, .Object@name)[[1]]
expectName <- paste(modelname, "expectation", sep=".")
expectation <- flatModel@expectations[[expectName]]
dataname <- expectation@data
return(flatModel)
})
setMethod("genericFitFunConvert", "MxFitFunctionGREML",
function(.Object, flatModel, model, labelsData, dependencies) {
.Object <- callNextMethod()
name <- .Object@name
modelname <- imxReverseIdentifier(model, .Object@name)[[1]]
expectName <- paste(modelname, "expectation", sep=".")
if (expectName %in% names(flatModel@expectations)) {
expectIndex <- imxLocateIndex(flatModel, expectName, name)
} else {
expectIndex <- as.integer(NA)
}
.Object@expectation <- expectIndex
if(length(.Object@dV)){
.Object@dV <- sapply(.Object@dV, imxLocateIndex, model=flatModel, referant=name)
}
if(length(.Object@aug)){.Object@aug <- imxLocateIndex(.Object@aug[1], model=flatModel, referant=name)}
if(length(.Object@augGrad)){
.Object@augGrad <- imxLocateIndex(.Object@augGrad[1], model=flatModel, referant=name)
}
if(length(.Object@augHess)){
.Object@augHess <- imxLocateIndex(.Object@augHess[1], model=flatModel, referant=name)
}
return(.Object)
})
setMethod("genericFitInitialMatrix", "MxFitFunctionGREML",
function(.Object, flatModel) {return(matrix(as.double(NA), 1, 1))})
setMethod("generateReferenceModels", "MxFitFunctionGREML",
function(.Object, model, distribution) {
stop("Reference models for GREML expectation are not implemented")
})
mxFitFunctionGREML <- function(
dV=character(0), aug=character(0), augGrad=character(0), augHess=character(0), autoDerivType=c("semiAnalyt","numeric"),
infoMatType=c("average","expected")){
autoDerivType = as.character(match.barg(autoDerivType,c("semiAnalyt","numeric")))
infoMatType = as.character(match.barg(infoMatType,c("average","expected")))
return(new("MxFitFunctionGREML",dV=dV,aug=aug,augGrad=augGrad,augHess=augHess,autoDerivType=autoDerivType,infoMatType=infoMatType))
}
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