For some of my current projects, I'm probably going to need to eventually estimate some models using Metropolis-Hastings sampling. I understand the basic concepts, and the software I use (R) has ...

In this paper, parametric and empirical likelihood functions or surfaces are compared. In particular, first- and second-order expansions for log likelihood functions are developed in nonparametric and ...

The need to combine likelihood information is common in analyses of complex models and in meta-analyses, where information is combined from several studies. We work to first order, and show that full ...

Empirical likelihood methods have emerged as a robust, non‐parametric framework for statistical inference that skilfully bypasses the need for strong parametric assumptions. By constructing likelihood ...