I am looking for a list of stochastic algorithms to approximate likelihoods.

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    $\begingroup$ Can you be more specific? $\endgroup$ – cardinal Nov 23 '11 at 22:12
  • $\begingroup$ If likelihood analytically very expensive or not able to calculate then the likelihood-free (approximate Bayesian computation (en.wikipedia.org/wiki/Approximate_Bayesian_computation) ) methods are available. I am looking for an alternative to such algorithm in domain of stochastic algorithms. $\endgroup$ – Biostat Nov 23 '11 at 22:39
  • $\begingroup$ What do you mean by "stochastic algorithms"? ABC is a stochastic algorithm since it relies on simulation. $\endgroup$ – Xi'an Nov 24 '11 at 8:51
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    $\begingroup$ You could try Googling 'simulated maximum likelihood'. I don't know anything about it myself beyond the name. $\endgroup$ – onestop Nov 24 '11 at 10:22
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    $\begingroup$ Indirect inference and ABC are very similar (see for instance the incoming <a href="rss.org.uk/uploadedfiles/userfiles/files/… Paper in JRSS B</a>). They both use simulation. So I am still unclear as to what you are precisely looking for. A way to maximise the likelihood rather than approximating the whole function? This would be the domain of simulated annealing methods. $\endgroup$ – Xi'an Nov 25 '11 at 8:08

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