Standard testing of mstats vs. stats results

This pull request has two purposes:

1) providing a framework for improved unittesting of mstats functions by comparing against stats functions
2) provide a variety of bugfixes for bugs I found in mstats, when comparing stats functions against mstats.

top #1:
I implemented a test class which allows unittesting the results between stats and mstats.
This work originated from the following this issue (https://github.com/scipy/scipy/issues/2318).

What you can do:
a) compare stats and mstats results in a consistent manner
b) print a table which gives you an overview about the routines which have already unittests implemented (use print_stats_mstats_comparison for this)

Results of the unittests indicate that for some routines in mstats there are bugs. I have initially commented these tests in the code, so the tests run properly through.

top #2:
While doing the unittesting, a couple of errors occured, which I could identify as bugs in mstats routines. I tried to fix them.
When doing the bugfixing I had also to add new arguments to a couple of routines. I ensured that the mstats routines remain backward compatible. As a result, the default arguments between mstats and stats routines somehow differ in some cases.