Thank you all for your input. Unfortunately my problem is not yet resolved. Before I respond to individual comments I make a clarification:
In Stata, using the same likelihood function as above, I can reproduce EXACTLY (to 3 decimal places or more, which is exactly considering I am using different software) the results from model 8 of the paper. I take this as an indication that I am using the same likelihood function as the authors, and that it does indeed work. The reason I am trying to estimate the model in R is because while Stata reproduces model 8 perfectly it has convergence difficulties for some of the other models. Peter Dalgaard, "Better starting values would help. In this case, almost too good values are available: start <- c(coef(lm(y1~x1+x2+x3)), coef(lm(y2~x1+x2+x3))) which appears to be the _exact_ solution." Thanks for the suggestion. Using these starting values produces the exact estimate that Dave Fournier emailed me. If these are the exact solution then why did the author publish different answers which are completely reproducible in Stata and Tsp? Ravi, Thanks for introducing optimx to me, I am new to R. I completely agree that you can get higher log-likelihood values than what those obtained with optim and the starting values suggested by Peter. In fact, in Stata, when I reproduce the results of model 8 to more than 3 dp I get a log-likelihood of 54.039139. Furthermore if I estimate model 8 without symmetry imposed on the system I reproduce the Likelihood Ratio reported in the paper to 3 decimal places as well, suggesting that the log-likelihoods I am reporting differ from those in the paper only due to a constant. Thanks for your comments, I am still highly interested in knowing why the results of the optimisation in R are so different to those in Stata? I might try making my convergence requirements more stringent. Kind regards, Alex ______________________________________________ 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.
