  In this paper a simple procedure to deal with label switching when exploring
complex posterior distributions by MCMC algorithms is proposed. Although it
cannot be generalized to any situation, it may be handy in many applications
because of its simplicity and very low computational burden. A possible area
where it proves to be useful is when deriving a sample for the posterior
distribution arising from finite mixture models when no simple or rational
ordering between the components is available.
