21 citations · 37 across the 10 of their papers we have counts for
11 papers
Regularized Exponentially Tilted Empirical Likelihood for Bayesian Inference
Eunseop Kim, Steven N. MacEachern, Mario Peruggia
Bayesian inference with empirical likelihood faces a challenge as the posterior domain is a proper subset of the original parameter space due to the convex hull constraint. We prop…
Familial inference: tests for hypotheses on a family of centres
Ryan Thompson, Catherine S. Forbes, Steven N. MacEachern +1
Statistical hypotheses are translations of scientific hypotheses into statements about one or more distributions, often concerning their centre. Tests that assess statistical hypot…
Empirical likelihood for the analysis of experimental designs
Eunseop Kim, Steven N. MacEachern, Mario Peruggia
Empirical likelihood enables a nonparametric, likelihood-driven style of inference without restrictive assumptions routinely made in parametric models. We develop a framework for a…
Empirical Bayes Model Averaging with Influential Observations: Tuning Zellner's g Prior for Predictive Robustness
Christopher M. Hans, Mario Peruggia, Junyan Wang
The behavior of Bayesian model averaging (BMA) for the normal linear regression model in the presence of influential observations that contribute to model misfit is investigated. R…
Asymptotics of Lower Dimensional Zero-Density Regions
Hengrui Luo, Steve N. MacEachern, Mario Peruggia
Topological data analysis (TDA) allows us to explore the topological features of a dataset. Among topological features, lower dimensional ones have recently drawn the attention of…
Rediscovering a little known fact about the t-test and the F-test: Algebraic, Geometric, Distributional and Graphical Considerations
Jennifer A. Sinnott, Steven N. MacEachern, Mario Peruggia
We discuss the role that the null hypothesis should play in the construction of a test statistic used to make a decision about that hypothesis. To construct the test statistic for…