3 papers
stat.ME2024
On an Empirical Likelihood based Solution to the Approximate Bayesian Computation Problem
Sanjay Chaudhuri, Subhroshekhar Ghosh, Kim Cuc Pham
Approximate Bayesian Computation (ABC) methods are applicable to statistical models specified by generative processes with analytically intractable likelihoods. These methods try t…
stat.OT2022
elhmc: An R Package for Hamiltonian Monte Carlo Sampling in Bayesian Empirical Likelihood
Dang Trung Kien, Neo Han Wei, Sanjay Chaudhuri
In this article, we describe a {\tt R} package for sampling from an empirical likelihood-based posterior using a Hamiltonian Monte Carlo method. Empirical likelihood-based methodol…
stat.ME2022
Population level information combined parameter estimation from complex survey datasets
Sanjay Chaudhuri, Mark S. Handcock, Michael S. Rendall
We consider an empirical likelihood framework for inference for a statistical model based on an informative sampling design and population-level information. The population-level i…