6 papers
A Bayesian Adaptive Latent Mixture Model for Zero-Inflated Weighted Brain Connectome Analysis
Hsin-Hsiung Huang, Yuh-Haur Chen, Teng Zhang
Replicated weighted networks often exhibit many structural zeros alongside heterogeneous non-zero edge strengths. In structural connectomics, this zero-inflation coincides with sub…
Bayesian low-rank latent-cluster regression for mixed health outcomes
Hsin-Hsiung Huang, Suyeon Kang
High-dimensional health and surveillance studies often involve many collinear predictors, multiple correlated outcomes of different types, and latent heterogeneity across observati…
HIMCE: High-dimensional multiple imputation via covariance-mode updating for neuroimaging and spatiotemporal blocks
Hsin-Hsiung Huang, Stef van Buuren
High-dimensional neuroimaging and spatiotemporal blocks often contain structured missingness from acquisition artifacts, preprocessing failures, and sensor dropout. Multiple imputa…
Bayesian sparse principal coordinates analysis with delta-tolerant linear approximation for microbiome data
Hsin-Hsiung Huang, Ruitao Liu, Liangliang Zhang +1
Principal coordinates analysis (PCoA) is a standard exploratory tool for microbiome beta-diversity studies, but its axes are defined by pairwise dissimilarities and therefore do no…
Bayesian Deep Count Regression and Anomaly Detection: Evidence from GDELT Event Panels
Hsin-Hsiung Huang, Yuh-Haur Chen, Mahlon Scott
The Global Database of Events, Language and Tone (GDELT) provides geolocated event records that can be aggregated into weekly spatiotemporal panels of event counts across regions,…
Low-Rank Regularization of Global Fréchet Regression Models for Distributional Responses
Kyunghee Han, Hsin-Hsiung Huang
Fréchet regression has emerged as a useful tool for modeling non-Euclidean response variables associated with Euclidean covariates. In this work, we propose a global Fréchet regr…