In this paper we consider Markov chains associated with the Metropolis-Hastings algorithm. We propose conditions under which the sequence of the successive densities of such a chain converges to the target density according to the total variation distance for any choice of the initial density. In particular we prove that the positiveness of the target and the proposal densities is enough for the chain to converge.
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