1 citations · 5 across the 9 of their papers we have counts for
5 papers · 1 filter
Comparing Two Categorical Gini Correlations with Applications to Classification Problems
Sameera Hewage, Yongli Sang
This article proposes an inferential framework for comparing predictor importance in classification problems with categorical response variables. The approach is based on the categ…
Bayesian Inference for Joint Tail Risk in Paired Biomarkers via Archimedean Copulas with Restricted Jeffreys Priors
Agnideep Aich, Md. Monzur Murshed, Sameera Hewage +1
We propose a Bayesian copula-based framework to quantify clinically interpretable joint tail risks from paired continuous biomarkers. After converting each biomarker margin to rank…
gcor: A Python Implementation of Categorical Gini Correlation and Its Inference
Sameera Hewage
Categorical Gini Correlation (CGC), introduced by Dang et al. (2020), is a novel dependence measure designed to quantify the association between a numerical variable and a categori…
A2 Copula-Driven Spatial Bayesian Neural Network For Modeling Non-Gaussian Dependence: A Simulation Study
Agnideep Aich, Sameera Hewage, Md Monzur Murshed +5
In this paper, we introduce the A2 Copula Spatial Bayesian Neural Network (A2-SBNN), a predictive spatial model designed to map coordinates to continuous fields while capturing bot…
Jackknife empirical likelihood confidence intervals for the categorical Gini correlation
Sameera Hewage, Yongli Sang
The categorical Gini correlation, , was proposed by Dang et al. to measure the dependence between a categorical variable, , and a numerical variable, . It has been show…