Features TBD:

* trim data( + min, max, ... )
* generate (random var with $self's distribution)
* total_abs_error, mean_abs_error - think more
* data inspection tools - allow user to look at real bin counts
* framework for sophisticated algorithms over data
* fix variance/stdev - make /(n+1) correction the default
* add normalization parameter to histogram (i.e. picture height)

Cleanup:

* more detailed docs on methods
* rationale

Features for discussion:

* better mode algorithm
* Additional module with smooth data model (more CPU, more precision, exact mean)
* how to find the bulk of a distribution
* C++/XS library
* analysis tools (like: Your sample looks like 45% normal (100, 15) + 35% exp (100) + 20% utter rubbish)

Multidimentional S::D::LogScale:
* linear/log storage
* correlation for 2D
* all other stuff
