Dana DeMaster

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All published works

Action	Title	Year	Authors
+	Bayesian varying‐effects vector autoregressive models for inference of brain connectivity networks and covariate effects in pediatric traumatic brain injury	2024	Yangfan Ren Nathan Osborne Christine B. Peterson Dana DeMaster Linda Ewing‐Cobbs Marina Vannucci
+ PDF Chat	Bayesian Varying-Effects Vector Autoregressive Models for Inference of Brain Connectivity Networks and Covariate Effects in Pediatric Traumatic Brain Injury	2024	Yangfan Ren Nathan Osborne Christine B. Peterson Dana DeMaster Linda Ewing‐Cobbs Marina Vannucci
+ PDF Chat	BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks	2020	Jeong Hwan Kook Kelly A. Vaughn Dana DeMaster Linda Ewing‐Cobbs Marina Vannucci

Common Coauthors

Coauthor	Papers Together
Marina Vannucci	3
Linda Ewing‐Cobbs	3
Yangfan Ren	2
Christine B. Peterson	2
Nathan Osborne	2
Jeong Hwan Kook	1
Kelly A. Vaughn	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	APPROACHES FOR BAYESIAN VARIABLE SELECTION	1997	Edward I. George Robert E. McCulloch	2
+ PDF Chat	Time varying undirected graphs	2010	Shuheng Zhou John Lafferty Larry Wasserman	1
+ PDF Chat	A sparse conditional Gaussian graphical model for analysis of genetical genomics data	2011	Jia‐Xin Yin Hongzhe Li	1
+	The ubiquitous Kronecker product	2000	Charles F. Van Loan	1
+	Bayesian fMRI data analysis with sparse spatial basis function priors	2007	Guillaume Flandin W.D. Penny	1
+	Computational methods for local regression	1991	William S. Cleveland Eric H. Grosse	1
+ PDF Chat	Sparse Estimation of Conditional Graphical Models With Application to Gene Networks	2012	Bing Li Hyonho Chun Hongyu Zhao	1
+ PDF Chat	Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables	2013	Nicholas G. Polson James G. Scott Jesse Windle	1
+	Variational Relevance Vector Machines	2013	Chris Bishop Michael E. Tipping	1
+	Temporal causal modeling with graphical granger methods	2007	Andrew O. Arnold Yan Liu Naoki Abe	1
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	1
+	Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem	2010	James G. Scott James O. Berger	1
+ PDF Chat	Estimating the Dimension of a Model	1978	Gideon Schwarz	1
+	Varying-Coefficient Models	1993	Trevor Hastie Robert Tibshirani	1
+	Variational Relevance Vector Machines	2013	Chris Bishop Michael E. Tipping	1
+ PDF Chat	Integrative Bayesian analysis of brain functional networks incorporating anatomical knowledge	2018	Ixavier A. Higgins Suprateek Kundu Ying Guo	1
+ PDF Chat	Estimating time-varying networks	2010	Mladen Kolar Le Song Amr Ahmed Eric P. Xing	1
+	Variational Inference: A Review for Statisticians	2017	David M. Blei Alp Kucukelbir Jon McAuliffe	1
+ PDF Chat	BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks	2020	Jeong Hwan Kook Kelly A. Vaughn Dana DeMaster Linda Ewing‐Cobbs Marina Vannucci	1
+ PDF Chat	Variational Bayes for High-Dimensional Linear Regression With Sparse Priors	2020	Kolyan Ray Botond Szabó	1
+	Integrative learning for population of dynamic networks with covariates	2021	Suprateek Kundu Ming Jin Joe Nocera Keith McGregor	1
+	Discrete Spike-and-Slab Priors: Models and Computational Aspects	2021	Marina Vannucci	1
+ PDF Chat	Scalable Variational Inference for Bayesian Variable Selection in Regression, and Its Accuracy in Genetic Association Studies	2012	Peter Carbonetto Matthew Stephens	1
+	plsmselect: Linear and Smooth Predictor Modelling with Penalisation and Variable Selection	2019	Indrayudh Ghosal Matthías Kormáksson	1