64 citations · 86 across the 9 of their papers we have counts for
9 papers
Novel Bayesian method for simultaneous detection of activation signatures and background connectivity for task fMRI data
Michelle F. Miranda, Jeffrey S. Morris
In this paper, we introduce a new Bayesian approach for analyzing task fMRI data that simultaneously detects activation signatures and background connectivity. Our modeling involve…
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…
Ordinal Probit Functional Outcome Regression with Application to Computer-Use Behavior in Rhesus Monkeys
Mark J. Meyer, Jeffrey S. Morris, Regina Paxton Gazes +1
Research in functional regression has made great strides in expanding to non-Gaussian functional outcomes, but exploration of ordinal functional outcomes remains limited. Motivated…
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…
Functional Regression
Jeffrey S. Morris
Functional data analysis (FDA) involves the analysis of data whose ideal units of observation are functions defined on some continuous domain, and the observed data consist of a sa…
Automated analysis of quantitative image data using isomorphic functional mixed models, with application to proteomics data
Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Richard C. Herrick +2
Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensiti…
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…