36 citations · 104 across the 18 of their papers we have counts for
20 papers
Robust distribution-free tests for the linear model
Torey Hilbert, Steven MacEachern, Yuan Zhang
Recently, there has been growing concern about heavy-tailed and skewed noise in biological data. We introduce RobustPALMRT, a flexible permutation framework for testing the associa…
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…
A Process of Dependent Quantile Pyramids
Hyoin An, Steven N. MacEachern
Despite the practicality of quantile regression (QR), simultaneous estimation of multiple QR curves continues to be challenging. We address this problem by proposing a Bayesian non…
Superset model problem
Koji Miyawaki, Steven N. MacEachern
This paper focuses on the superset model problem that arises in the context of regression. To address this problem, we take the Bayesian approach to measure its uncertainty. An ill…
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…