On some method for diagnosing convergence in MCMC setups via atoms and renewal sets

MCMC setups are among the best known methods for conducting computer simulations necessary in statistics, physics, biology, etc. However, to obtain appropriate solutions, additional convergence diagnosis must be applied for trajectory generated by Markov Chain. In the paper we present, the method for dealing with this problem, based on features of so called "secondary" chain (the chain with specially selected state space). The secondary chain is created from the initial chain by picking only some observations connected with atoms or renewal sets. The discussed method has some appealing properties, like high degree of diagnosis automation. Apart from theoretical lemmas, the example of application is also provided.