4 papers
Uncertainty-Aware Ideal Point Estimation via Variational EM
Kwangok Seo, Youngjo Lee, Jong Hee Park +2
Roll-call data analysis aims to estimate legislators' ideal points and quantify the associated uncertainty. Existing approaches either rely on Bayesian methods implemented via Mark…
Subject-specific Deep Neural Networks for Count Data with High-cardinality Categorical Features
Hangbin Lee, Il Do Ha, Changha Hwang +1
There is a growing interest in subject-specific predictions using deep neural networks (DNNs) because real-world data often exhibit correlations, which has been typically overlooke…
Point Mass in the Confidence Distribution: Is it a Drawback or an Advantage?
Hangbin Lee, Youngjo Lee
Stein's (1959) problem highlights the phenomenon called the probability dilution in high dimensional cases, which is known as a fundamental deficiency in probabilistic inference. T…
Statistical Inference for Random Unknowns via Modifications of Extended Likelihood
Hangbin Lee, Youngjo Lee
Fisher's likelihood is widely used for statistical inference for fixed unknowns. This paper aims to extend two important likelihood-based methods, namely the maximum likelihood pro…