fatvegan

I've been using Stata's ml command for a while now. It's all quite nifty, but I couldn't figure out how to use the ml init part and I had a feeling that it would be a useful sort of command. When your likelihood function isn't globally concave there are no guarantees you're going to find the maximum you're looking for. The manual was pretty terse, and the book that explains it is $180 so I had just ignored it. But after running out of other options I started scouring the web for some example of it. And it's actually dead simple.

ml init beta:index=1 beta:_cons=0 /a=-4.566654 /b=-1.332323 /c=-0.54343

There is one equation and three parameters. All this command is saying that assume the coefficient on only regressor (mrw_index) is going to be in vicinity of 1 and the intercept in the vicinity of 0.

In this example the model failed to converge after 3 iterations with the hints and failed after 13 iterations without the hints. And that seems like a great improvement.

It's remarkable how exciting it can be just watching numbers trickle past and slowly converge.

I keep forgetting how to set the ado install path, when you don't have write access to the default path. This is it.

sysdir set PLUS youradopath

You'd use it if you get an error like this when you try to install new libraries:

could not rename c:\ado\plus\stata.trk to c:\ado\plus\backup.trk

I found some issues with Stata's leastlikely command, so I fixed it up a bit. If you're getting issues with missing brackets, or failed to generate "Prob" or the error option outcome() not allowed then this will probably help. It's called leastlikely2, but you can rename it.

I also found that to give it a variable to put the probabilities into, you need to give it a previously generated variable.

gen pr = .
leastlikely2, generate(pr)

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