use diagonal entries on covariance matrix if eigen decomposition fails (this is in MCMC)
guard against negative covariance
if eigen vector code does not throw an exception, but the maxerr is too large, just use the diagonal covariances
clarified a print statement
added a bunch of throws to the eigen and mcmc code to deal with nan eigenvectors or eigenvalues
guard against zero indepdendent samples in mcmc_extractor.cpp
made degen a global variable so we can account for it when calculating acceptance rate
change name of diagnostic file in mcmc_test
implemented gibbs search
added mcmc_extraction_runner.cpp
calculate covariance matrix at least once, regardless of acceptance ratio
now alternate between calculating covariance matrix and adjusting p_factor