3 papers
stat.ME2026
Variable Selection in Functional Linear Quantile Regression for Identifying Associations between Daily Patterns of Physical Activity and Cognitive Function
Yuanzhen Yue, Stella Self, Yichao Wu +2
Quantile regression is useful for characterizing the conditional distribution of a response variable and understanding heterogeneity in the covariate effects at different quantiles…
stat.ME2024
Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional regression
Anja Zgodic, Ray Bai, Jiajia Zhang +3
Sparse linear regression methods for high-dimensional data commonly assume that residuals have constant variance, which can be violated in practice. For example, Aphasia Quotient (…
stat.ME2024
Sparse high-dimensional linear mixed modeling with a partitioned empirical Bayes ECM algorithm
Anja Zgodic, Ray Bai, Jiajia Zhang +2
High-dimensional longitudinal data is increasingly used in a wide range of scientific studies. To properly account for dependence between longitudinal observations, statistical met…