5 papers
Bayesian Edge Regression in Undirected Graphical Models to Characterize Interpatient Heterogeneity in Cancer
Zeya Wang, Veera Baladandayuthapan, Ahmed O. Kaseb +4
Graphical models are commonly used to discover associations within gene or protein networks for complex diseases such as cancer. Most existing methods estimate a single graph for a…
Regression Analyses of Distributions using Quantile Functional Regression
Hojin Yang, Veerabhadran Baladandayuthapani, Arvind U. K. Rao +1
Radiomics involves the study of tumor images to identify quantitative markers explaining cancer heterogeneity. The predominant approach is to extract hundreds to thousands of image…
Function-on-Scalar Quantile Regression with Application to Mass Spectrometry Proteomics Data
Yusha Liu, Meng Li, Jeffrey S. Morris
Mass spectrometry proteomics, characterized by spiky, spatially heterogeneous functional data, can be used to identify potential cancer biomarkers. Existing mass spectrometry analy…
Quantile Functional Regression using Quantlets
Hojin Yang, Veerabhadran Baladandayuthapani, Jeffrey S. Morris
In this paper, we develop a quantile functional regression modeling framework that models the distribution of a set of common repeated observations from a subject through the quant…
Online Variational Bayes Inference for High-Dimensional Correlated Data
Sylvie Tchumtchoua, David B. Dunson, Jeffrey S. Morris
High-dimensional data with hundreds of thousands of observations are becoming commonplace in many disciplines. The analysis of such data poses many computational challenges, especi…