36 citations · 88 across the 12 of their papers we have counts for
12 papers
A joint model of the individual mean and within-subject variability of a longitudinal outcome with a competing risks time-to-event outcome
Shanpeng Li, Daniel S. Nuyujukian, Robyn L. McClelland +4
Motivated by a growing body of research emphasizing the importance of modeling within-subject (WS) variability in longitudinal biomarkers and its association with health outcomes,…
Efficient Algorithms and Implementation of a Semiparametric Joint Model for Longitudinal and Competing Risks Data: With Applications to Massive Biobank Data
Shanpeng Li, Ning Li, Hong Wang +3
Semiparametric joint models of longitudinal and competing risks data are computationally costly and their current implementations do not scale well to massive biobank data. This pa…
DistStat.jl: Towards Unified Programming for High-Performance Statistical Computing Environments in Julia
Seyoon Ko, Hua Zhou, Jin Zhou +1
The demand for high-performance computing (HPC) is ever-increasing for everyday statistical computing purposes. The downside is that we need to write specialized code for each HPC…
Extensions to the Proximal Distance Method of Constrained Optimization
Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou +1
The current paper studies the problem of minimizing a loss subject to constraints of the form , where is a closed set, c…
High-Performance Statistical Computing in the Computing Environments of the 2020s
Seyoon Ko, Hua Zhou, Jin J. Zhou +1
Technological advances in the past decade, hardware and software alike, have made access to high-performance computing (HPC) easier than ever. We review these advances from a stati…
Probabilistic Error Analysis for Inner Products
Ilse C. F. Ipsen, Hua Zhou
Probabilistic models are proposed for bounding the forward error in the numerically computed inner product (dot product, scalar product) between of two real -vectors. We derive…
Matrix Linear Discriminant Analysis
Wei Hu, Weining Shen, Hua Zhou +1
We propose a novel linear discriminant analysis approach for the classification of high-dimensional matrix-valued data that commonly arises from imaging studies. Motivated by the e…
Provable Convex Co-clustering of Tensors
Eric C. Chi, Brian R. Gaines, Will Wei Sun +2
Cluster analysis is a fundamental tool for pattern discovery of complex heterogeneous data. Prevalent clustering methods mainly focus on vector or matrix-variate data and are not a…
MM Algorithms for Variance Component Estimation and Selection in Logistic Linear Mixed Model
Liuyi Hu, Wenbin Lu, Jin Zhou +1
Logistic linear mixed model is widely used in experimental designs and genetic analysis with binary traits. Motivated by modern applications, we consider the case with many groups…
Algorithms for Fitting the Constrained Lasso
Brian R. Gaines, Hua Zhou
We compare alternative computing strategies for solving the constrained lasso problem. As its name suggests, the constrained lasso extends the widely-used lasso to handle linear co…
Tensor Generalized Estimating Equations for Longitudinal Imaging Analysis
Xiang Zhang, Lexin Li, Hua Zhou +2
In an increasing number of neuroimaging studies, brain images, which are in the form of multidimensional arrays (tensors), have been collected on multiple subjects at multiple time…
Tucker Tensor Regression and Neuroimaging Analysis
Xiaoshan Li, Hua Zhou, Lexin Li
Large-scale neuroimaging studies have been collecting brain images of study individuals, which take the form of two-dimensional, three-dimensional, or higher dimensional arrays, al…