ENH: Add k-sample Anderson-Darling test to stats module
API: Speed up and implement both version for discrete distributions for k-sample Anderson-Darling test

1. Change call signature to have array of arrays and optional keyword to
   specify which version of the k-sample AD test should be computed.

2. Get rid of all inner loops and list comprehensions by using
   np.searchsorted.

3. Both version given by Scholz & Stephens for discrete sample can be
   computed now.
MAINT: address review comments on stats.anderson_ksamp addition.

Changes:
STY: Replace "&" with "and: in citation and add year in stats.anderson_ksamp
     and stats.__anderson_ksamp_both
MAINT: fix typo in docstring stats.anderson_ksamp
STY: add blank lines after if blocks in k-sample Anderson Darling routines
STY: Use ... for line continuation in docstring in stats.anderson_ksamp
DOC: Add comment to explain interpolation values stats.anderson_ksamp
STY: capital letter for each parameter description and period at end in
     k-sample Anderson-Darling docstrings
MAINT: combine a few simple statements in stats.anderson_ksamp
API: Change call signature of stats.anderson_ksamp

- Replace discrete=False with midrank=True to better explain what the
  difference between tests is. Update the docstrings accordingly.
MAINT: avoid computation of lj for continuous dists in stats._anderson_ksamp_midrank.

Also fix docstring for parameters.
TST: fix test failure for stats.anderson_ksamp with numpy 1.5.x

Due to ``np.testing.assert_warns`` returning None for that numpy version.
Merge branch 'pr/3183' into master.

Review at https://github.com/scipy/scipy/pull/3183