A Quasi likelihood approximation of posterior distributions for likelihood-intractable complex models Articles uri icon

published in

publication date

  • August 2014

start page

  • 153

end page

  • 167

issue

  • 2

volume

  • 72

international standard serial number (ISSN)

  • 0026-1424

electronic international standard serial number (EISSN)

  • 2281-695X

abstract

  • Complex models typically involve intractable likelihood functions which, from a Bayesian perspective, lead to intractable posterior distributions. In this context, Approximate Bayesian computation (ABC) methods can be used in order to obtain a valid posterior approximation. However, when simulation from the model is computationally demanding, then the ABC approach may be cumbersome. We discuss an alternative method, where the intractable likelihood is approximated by a quasi-likelihood calculated through an algorithm that is reminiscent of the ABC. The proposed approximation method requires less computational effort than ABC. An extension to multiparameter models is also considered and the method is illustrated by several examples. © Sapienza Universitá di Roma 2014.

keywords

  • estimating equations; likelihood-free methods; pseudo-likelihoods; summary statistics