optimizers called by sem. The user would not
normally call these functions directly, but rather supply one of them in the objective argument to
sem. Users may also write their own objective functions. objectiveML and objectiveML2 are for multinormal maximum-likelihood
estimation; objectiveGLS and objectiveGLS2 are for generalized least squares. objectiveML and objectiveGLS use
compiled code and are therefore substantially faster. objectiveML2 and objectiveGLS2 are provided primarily to illustrate
how to write sem objective functions in R. msemObjectiveML uses compiled code is for fitting multi-group models by
multinormal maximum likelihood; msemObjectiveML2 is similar but doesn't use compiled code. msemObjectiveGLS uses compiled
code and is for fitting multi-group models by generalized least squares.objectiveML(gradient=TRUE, hessian=FALSE)
objectiveML2(gradient=TRUE)
objectiveGLS(gradient=FALSE)
objectiveGLS2(gradient=FALSE)
msemObjectiveML(gradient=TRUE)
msemObjectiveML2(gradient=TRUE)
msemObjectiveGLS(gradient=FALSE)TRUE, the object that's returned includes a function for computing an analytic gradient; there is at present no
analytic gradient available for objectiveGLS, objectiveGLS2, or msemObjectiveGL.TRUE, the objected returned includes a function to compute an analytic Hessian; only avaiable for objectiveML
and not generally recommended."semObjective", with up to two elements:sem.sem, optimizers