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library(OpenMx)
library(testthat)
context("Legacy Multiple Group WLS")

skip_on_cran()

# Simulate some data

x=rnorm(1000, mean=0, sd=1)
y= 0.5*x + rnorm(1000, mean=0, sd=1)
tmpFrame <- data.frame(x, y)
tmpNames <- names(tmpFrame)
wdata <- mxDataWLS(tmpFrame, type="DWLS")

# Define the matrices

S <- mxMatrix(type = "Full", nrow = 2, ncol = 2, values=c(1,0,0,1),
              free=c(TRUE,FALSE,FALSE,TRUE), labels=c("Vx", NA, NA, "Vy"), name = "S")
A <- mxMatrix(type = "Full", nrow = 2, ncol = 2, values=c(0,1,0,0),
              free=c(FALSE,TRUE,FALSE,FALSE), labels=c(NA, "b", NA, NA), name = "A")
I <- mxMatrix(type="Iden", nrow=2, ncol=2, name="I")

# Define the expectation

expCov <- mxAlgebra(solve(I-A) %*% S %*% t(solve(I-A)), name="expCov")
expFunction <- mxExpectationNormal(covariance="expCov", dimnames=tmpNames)

# Choose a fit function

fitFunction <- mxFitFunctionWLS()

# Define the model

tmpModel <- mxModel(model="exampleModel", S, A, I, expCov, expFunction, fitFunction,
                    wdata, mxCI("A"))

# Fit the model and print a summary

tmpModelOut <- mxRun(tmpModel)
summary(tmpModelOut)

tmpModel2 <- mxModel(tmpModel,name="tmp2")
twoGroup <- mxModel("two", tmpModel, tmpModel2, mxFitFunctionMultigroup(c("exampleModel","tmp2")))
twoGroup <- mxRun(twoGroup)

# Experiment with multigroup automatic start values
autModel1 <- mxModel(tmpModel, name="auto1", mxData(tmpFrame, 'raw'),
	mxMatrix(name='expMean', nrow=1, ncol=2, free=TRUE),
	mxExpectationNormal(covariance="expCov", means='expMean', dimnames=tmpNames),
	mxFitFunctionML())
autModel2 <- mxModel(autModel1, name="auto2")
autGroup <- mxModel("group", autModel1, autModel2, mxFitFunctionMultigroup(c("auto1","auto2")))
autStart <- mxAutoStart(autGroup)

# Starting values from mxAutoStart are close to the final estimates from multigroup WLS
omxCheckCloseEnough(coef(autStart)[names(coef(twoGroup))], coef(twoGroup), 1e-2)