(wip) [variational] lower likelihood bound
(wip) [cluster] Complete variational Bayes and VBmerge likelihood bound

o bound computation stable but doesn't always increase => test case fails
o doc includes default values, dimensions of arrays
o split into E- and M-step, perform E step first to allow consistent bound computation
o regularize responsibility to avoid overflows in log(0)
o simplify prune with getattr
o _expect_log_p_Z simplified
o E step and M step identical except for overloading
o return mode of variational posterior as result
o remove clumsy (and false) caching of intermediate constants

Bug fixes:
o m0[k] -> m0
o second part of covariance added to _update_W
o fix signs in bound
o user right Dirichlet B and C
o alpha0 vector and scalar disentangled
[markov_chain]  - bugfix in _get_log_rho_metropolis_hastings
[markov_chain] - bugfix: merge between log_target and indicator corrected
[doc/conf.py] -version is now read off file _version.py

[cluster/gaussian_mixture.py] - found unresolved bug in
                                GaussianMixture.__iter()
introduced submodule pmc
[pmc/proposal] - first version of class MixtureProposal
[pmc/proposal] introduced GaussianComponent
[pmc/proposal]  - introduced StudentTComponent
                - made some docstrings raw strings
                - extended tests
[markov_chain]      - corrected docstring in class Markov_Chain
[indicator_factory] - extracted from markov_chain to be a standalone
                      submodule
[markov_chain]  - moved method "_merge_target_with_indicator"
                  to _tools._chain
[pmc]  - implemented importance sampling