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Generalized Likelihood Maximization / Score Functions

Open patrickeganfoley opened this issue 11 years ago • 1 comments

I'm writing some code for a special case of generalized likelihood maximization. To do this, I have functions

score(noise::Distribution, theta, observations)

and

information(noise::Distribution, theta, observations)

which implement the first and second derivative of a distribution's loglikelihood w/r/t its parameters. I use these so I can run a version of Fisher Scoring on several models. Are there plans to include first and second derivatives in some part of Stats in Julia?

patrickeganfoley avatar Jan 24 '14 03:01 patrickeganfoley

This could be cool to do.

johnmyleswhite avatar Jan 24 '14 03:01 johnmyleswhite