#optim package
estimate<-optim(init.par,Linn,hessian=TRUE, method=c("L-BFGS-B"),control =
list(trace=1,abstol=0.001),lower=c(0,0,0,0,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf),upper=c(1,1,1,1,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf))#nlminb package estimate<-nlminb(init.par,Linn,gr=NULL,hessian=TRUE,control = list(trace=1,factr=1),lower=c(0,0,0,0,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf,-Inf),upper=c(1,1,1,1,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf,Inf)) I did not get same results from above equations. Log-likelihood values are close but parameter estimation completely different. My expectation is very close to "nlminb" packages. Do you have any idea and suggestion between packages? Regards, Serdar -- View this message in context: http://r.789695.n4.nabble.com/optim-and-nlminb-tp4645772.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
