burn-in and sample thinning to MCMC

- add `burnin` parameter specifying the number of burn-in steps
- add `thin` parameter specifying the sample collecting period
- add `nsamples` slot and method to MgsaResults class
tweak Gibbs step frequencies

To better explore the space of sets on/off states,
sets toggling step frequency is increased to 80%,
parameter sampling is down to 20%
randomize initial set states

to ensure that chains converge to a stationary state,
each MCMC starts with random on/off set states.
to avoid a,b and p parameters degeneration, parameters
sampling is disabled for the half of burn-in period,
only set states are toggled
cleanup mgsa()

- mgsa.wrapper() is the only place where default parameter values are defined
- mgsa() generic is the only place where the parameters are documented
- use ... in all other mgsa-related calls instead of explicitly listing all parameters
add mcmc_params struct

put all MCMC parameters into mcmc_params struct
add flip.freq parameter for MCMC

flip.freq is the frequency of Gibbs steps that flip a set of
random set from active into inactive or vice versa
add test to check mgsa() can run
Merge branch 'alyst/enhance_mcmc'
Include omp.h later.

SUPPORT_OPENMP is defined in one of the
R includes.
Bumped date und version.