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This happens because in some cases we cannot distinguish the posterior kernel and the likelihood. You will get this kind of plots if the likelihood is picked in a region where the prior is flat.
Thank you for your answer. I am sorry, but I have another stupid question. Is it possible that this problem induces the result of 0 standard deviation in the posterior maximization? Which could be the causes of this problem? What I have to do? Thank you so much, Chiara
No, these issues are not related... Zero posterior standard deviations are generally a consequence of a failure of the optimization step. You may try the following:
(1) Change the initial condition of the optimization routine (default is the prior mode) (2) Change the priors (3) Change the optimization routine