Add support to derive distribution properties from iterators

[hpux735]

This package is great, and it's most of what I need. However, there doesn't seem to be a way to give it an iterator and have it derive the distribution coefficients. For example, if you created a new Gaussian distribution, you could initialize it with an iterator over f64 and it would traverse the iterator and compute the mean and variance, which could then be used in later computation.

If there is interest in such a feature from the maintainer(s), and a desire to help shape the architecture of such a feature, I could take a crack at implementing it...

Let me know.

Thanks.

[IvanUkhov]

Hello, sorry for the late response!

Yes, I suppose estimation of distribution parameters would fit this crate. One could try it out on, say, Gaussian and see what abstractions would be needed. I am just thinking that there could be several cases, such as with and without known variance, and it would be nice to find good common traits to use across the crate. Perhaps one could start with one trait that tackles all parameters that the distribution in question has.

Please feel free to open a PR to discuss if you have time.

[hpux735]

Hi there. That sounds good. Here's a PR I created with what I had in mind. Feedback is welcome #33