which condition of the markov chain is the best to find convergence? what is theorem for total variation what is the difference between total variation and kml divergence which type of variation is stronger for a markov chain than total variation? how do markov chains converge? how do markov chains converge what is the difference between total variation and total variation in a continuous-state chain when do the markov chain converge does kl divergence depend on total variation? why does total variation differ from total variation when markov chain convergence which theorem describes the possibility a Markov chain could be a k-divergent chain? when does kl divergence occur in continuous state why does the markov chain convergence do markov chains converge why do markov chains converge in total variation what kind of variation can markov chains form which theorem describes the convergentness of a Markov chain? which of the following describes the convergent state of a markov chain? which is a condition that enables total variation in markov chaining? which theorem does it say that a chain of markov chains converges in the total variation?