68 citations · 172 across the 7 of their papers we have counts for
7 papers
Scalable Semiparametric Spatio-temporal Regression for Large Data Analysis
Ting Fung Ma, Fangfang Wang, Jun Zhu +2
With the rapid advances of data acquisition techniques, spatio-temporal data are becoming increasingly abundant in a diverse array of disciplines. Here we develop spatio-temporal r…
Control variates and Rao-Blackwellization for deterministic sweep Markov chains
Stephen Berg, Jun Zhu, Murray K. Clayton
We study control variate methods for Markov chain Monte Carlo (MCMC) in the setting of deterministic sweep sampling using transition kernels. New variance reduction resul…
Spatial Process Decomposition for Quantitative Imaging Biomarkers Using Multiple Images of Varying Shapes
ShengLi Tzeng, Jun Zhu, Amy Weisman +2
Quantitative imaging biomarkers (QIB) are extracted from medical images in radiomics for a variety of purposes including noninvasive disease detection, cancer monitoring, and preci…
Statistically-estimated tree composition for the northeastern United States at the time of Euro-American settlement
Christopher J. Paciorek, Simon J. Goring, Andrew L. Thurman +6
We present a gridded 8 km-resolution data product of the estimated composition of tree taxa at the time of Euro-American settlement of the northeastern United States and the statis…
Local Adaptive Grouped Regularization and its Oracle Properties for Varying Coefficient Regression
Wesley Brooks, Jun Zhu, Zudi Lu
Varying coefficient regression is a flexible technique for modeling data where the coefficients are functions of some effect-modifying parameter, often time or location in a certai…
Penalized maximum likelihood estimation and variable selection in geostatistics
Tingjin Chu, Jun Zhu, Haonan Wang
We consider the problem of selecting covariates in spatial linear models with Gaussian process errors. Penalized maximum likelihood estimation (PMLE) that enables simultaneous vari…