Fit Distributions Software

Anything I write myself, followed by anything I can get the source code for.
Software that hides what it is doing has limited use in science.

 

You can't be serious.

People use software packages all the time that do routines that we trust where we do not have the full source code. You think we have the source code for Mathematica, Maple, SPSS, SAS, MATLAB, JMP and so on?

For the OP look at some statistical packages which may do it for common distributions.

If your distribution is not supported one idea would be to use a chi-square goodness of fit test.

 

When I last used matlab, you could look in the m-files but not at the engine.

For my thesis I would set up the simulations in matlab or gnu/octave and when I thought I had something I would convert the whole thing to C.

I had colleagues who were always getting caught out by some little wrinkle that matlab or whatever did not handle quite right.

What you use depends on what you want to do - how important is it and how much scrutiny will it be subject to? But the very best, which was the question, is going to be specifically tailored to the task and completely transparent .. eg. something you wrote yourself (or hired someone better than you to write for you.)

You don't need the source code if you don't expect to get any unusual results. But if someone is likely to ask if what you found is really there or just an artifact of the computer program - you need the source. For publishes science you need, on hand, everything another researcher needs to duplicate your results.

These days gnu/octave fits my needs ... especially with the power of modern computers. The skills using it translate to other scripting languages. I know people who swear by spreadsheets ... which I personally find painful.