Hi everyone, I am looking for some recommended reading.
I want to read up on the estimation systems of linear equations using maximum likelihood? I have a strongly applied bias, I want to be able to do such estimation myself. Reading with examples would be great. Something which also works through a concentrated maximum likelihood estimation would be even better! I want to use a likelihood ratio test to compare some nested models of linear simultaneous equations. I have estimated the systems using systemfit() and nlsystemfit(). systemfit() can be used with lrtest() which automatically obtains the log-likelihood values. Unfortunately one of my models requires nonlinear coefficient restrictions and lrtest() does not seem to be usable with nlsystemfit(). I decided it would be a good idea to program the likelihood estimation myself. This would solve the problem and would also be a great learning experience. All suggestions will be highly appreciated! Thanks a lot, Alex Olssen Motu Economic and Public Policy Research Wellington New Zealand ______________________________________________ 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.
