721
Nicole A. Lazar
Empirical likelihood has been suggested as a data-based, nonparametric
alternative to the usual likelihood function. Research has shown that
empirical likelihood tests have many of the same asymptotic properties
as those derived from parametric likelihoods. This leads naturally to
the possibility of using empirical likelihood as the basis for
Bayesian inference. Different ways in which this goal might be
accomplished are considered. The validity of the resultant posterior
inferences is examined, as are frequentist properties of the Bayesian
empirical likelihood intervals.
Keywords: Alternative Likelihoods, Bayesian Inference, Nonparametric Inference