Approximate Bayesian computation with composite score functions

@article{Ruli2016ApproximateBC,
  title={Approximate Bayesian computation with composite score functions},
  author={Erlis Ruli and Nicola Sartori and Laura Ventura},
  journal={Statistics and Computing},
  year={2016},
  volume={26},
  pages={679-692}
}
Both approximate Bayesian computation (ABC) and composite likelihood methods are useful for Bayesian and frequentist inference, respectively, when the likelihood function is intractable. We propose to use composite likelihood score functions as summary statistics in ABC in order to obtain accurate approximations to the posterior distribution. This is motivated by the use of the score function of the full likelihood, and extended to general unbiased estimating functions in complex models… Expand

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