Summary statistics

v1.0.1a, 8/26/2014 --
(1) Distribution inertia added for all distributions. This means that
parameters for the distributions are updated to be
inertia*prior_parameters + (1-inertia)*new_parameters. This can be
triggered using `distribution_inertia` in the
`Model.train` method.

(2) Summary statistics implemented for Baum-Welch training. This
involves summarizing one sequence at a time and storing
the appropriate summary statistics to the distribution object using
`Distribution.summarize( items, weights )`, and then
updating the parameters using these summary statistics and an
appropriate inertia with `Distribution.from_summarize(
inertia=0.0 )`. This makes training on large numbers of sequences always
faster, but training on small numbers of long
sequences take slightly longer.

(3) Nosetests significantly expanded to include more tests. This
includes a new file `test_training.py`, which has a
large number of tests on the Viterbi and Baum-Welch training algorithms,
with different parameters. This also includes
expanded testing of each distribution, and each of the training
functions for that sample.