Marina Vannucci

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All published works

Action	Title	Year	Authors
+ PDF Chat	Bayesian Functional Graphical Models with Change-Point Detection	2025	Chunshan Liu Daniel R. Kowal James Doss‐Gollin Marina Vannucci
+	Tensor Decision Trees For High-Resolution Imaging Data	2024	Zhihao Chen Hengrui Luo Suprateek Kundu Marina Vannucci
+ PDF Chat	Bayesian Controlled FDR Variable Selection via Knockoffs	2024	Lorenzo Focardi-Olmi Anna Gottard Michele Guindani Marina Vannucci
+ PDF Chat	Bayesian network-guided sparse regression with flexible varying effects	2024	Yangfan Ren Christine B. Peterson Marina Vannucci
+ PDF Chat	Clustering computer mouse tracking data with informed hierarchical shrinkage partition priors	2024	Ziyi Song Weining Shen Marina Vannucci Alexandria Baldizon Paul M. Cinciripini Francesco Versace Michele Guindani
+ PDF Chat	Bayesian Bivariate Conway-Maxwell-Poisson Regression Model for Correlated Count Data in Sports	2024	Mauro Florez Michele Guindani Marina Vannucci
+ PDF Chat	Bayesian Covariate-Dependent Graph Learning with a Dual Group Spike-and-Slab Prior	2024	Zijian Zeng Meng Li Marina Vannucci
+ PDF Chat	Bayesian bivariate Conway–Maxwell–Poisson regression model for correlated count data in sports	2024	Mauro Florez Michele Guindani Marina Vannucci
+ PDF Chat	Bayesian sparse vector autoregressive switching models with application to human gesture phase segmentation	2024	Beniamino Hadj-Amar Jack Jewson Marina Vannucci
+ PDF Chat	Local Level Dynamic Random Partition Models for Changepoint Detection	2024	Alice Giampino Michele Guindani Bernardo Nipoti Marina Vannucci
+ PDF Chat	Bayesian network-guided sparse regression with flexible varying effects	2024	Yangfan Ren Christine B. Peterson Marina Vannucci
+	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 temporal biclustering with applications to multi-subject neuroscience studies	2024	Federica Zoe Ricci Erik B. Sudderth Jaylen Lee Megan A. K. Peters Marina Vannucci Michele Guindani
+	Bayesian Tensor Modeling for Image-based Classification of Alzheimer’s Disease	2024	Rongke Lyu Marina Vannucci Suprateek Kundu
+ PDF Chat	Discrete Autoregressive Switching Processes in Sparse Graphical Modeling of Multivariate Time Series Data	2024	Beniamino Hadj-Amar Aaron M. Bornstein Michele Guindani Marina Vannucci
+ PDF Chat	A Bayesian Nonparametric Approach for Clustering Functional Trajectories over Time	2024	Mingrui Liang Matthew D. Koslovsky Emily T. Hébert Darla E. Kendzor Marina Vannucci
+ PDF Chat	A predictor-informed multi-subject bayesian approach for dynamic functional connectivity	2024	Jaylen Lee Sana Hussain Ryan Warnick Marina Vannucci Isaac Menchaca Aaron R. Seitz Xiaoping Hu Megan A. K. Peters Michele Guindani
+ PDF Chat	Bayesian Functional Graphical Models with Change-Point Detection	2024	Chunshan Liu Daniel R. Kowal James Doss‐Gollin 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	Semiparametric Latent ANOVA Model for Event-Related Potentials	2024	Cheng-Han Yu Meng Li Marina Vannucci
+ PDF Chat	Semiparametric Bayesian Inference for Local Extrema of Functions in the Presence of Noise	2024	Meng Li Zejian Liu Cheng-Han Yu Marina Vannucci
+ PDF Chat	A Bayesian joint model for compositional mediation effect selection in microbiome data	2023	Jingyan Fu Matthew D. Koslovsky Andreas M. Neophytou Marina Vannucci
+ PDF Chat	Functional Concurrent Regression Mixture Models Using Spiked Ewens-Pitman Attraction Priors	2023	Mingrui Liang Matthew D. Koslovsky Emily T. Hébert Michael S. Businelle Marina Vannucci
+	Bayesian non-homogeneous hidden Markov model with variable selection for investigating drivers of seizure risk cycling	2023	Emily T. Wang Sharon Chiang Zulfi Haneef Vikram R. Rao Robert Moss Marina Vannucci
+	Bayesian Sparse Vector Autoregressive Switching Models with Application to Human Gesture Phase Segmentation	2023	Beniamino Hadj-Amar Jack Jewson Marina Vannucci
+	Semiparametric Latent ANOVA Model for Event-Related Potentials	2023	Cheng-Han Yu Meng Li Marina Vannucci
+	Bayesian Tensor Modeling for Image-based Classification of Alzheimer's Disease	2023	Rongke Lyu Marina Vannucci Suprateek Kundu
+ PDF Chat	Bayesian Image-on-Scalar Regression with a Spatial Global-Local Spike-and-Slab Prior	2022	Zijian Zeng Meng Li Marina Vannucci
+ PDF Chat	Bayesian Inference for Stationary Points in Gaussian Process Regression Models for Event-Related Potentials Analysis	2022	Cheng-Han Yu Meng Li Colin Noe Simon Fischer‐Baum Marina Vannucci
+	Bayesian Non-Homogeneous Hidden Markov Model with Variable Selection for Investigating Drivers of Seizure Risk Cycling	2022	Emily T. Wang Sharon Chiang Zulfi Haneef Vikram Rao Robert A. Moss Marina Vannucci
+	Bayesian Image-on-Scalar Regression with a Spatial Global-Local Spike-and-Slab Prior	2022	Zijian Zeng Meng Li Marina Vannucci
+	A Bayesian Joint Model for Compositional Mediation Effect Selection in Microbiome Data	2022	Jingyan Fu Matthew D. Koslovsky Andreas M. Neophytou Marina Vannucci
+	A Predictor-Informed Multi-Subject Bayesian Approach for Dynamic Functional Connectivity	2022	Jaylen Lee Sana Hussain Ryan Warnick Marina Vannucci Isaac Menchaca Aaron R. Seitz Xiaoping Hu Megan A. K. Peters Michele Guindani
+	Handbook of Bayesian Variable Selection	2021	Mahlet G. Tadesse Marina Vannucci
+	Discrete Spike-and-Slab Priors: Models and Computational Aspects	2021	Marina Vannucci
+	Latent Network Estimation and Variable Selection for Compositional Data Via Variational EM	2021	Nathan Osborne Christine B. Peterson Marina Vannucci
+ PDF Chat	Evidence of state-dependence in the effectiveness of responsive neurostimulation for seizure modulation	2021	Sharon Chiang Ankit N. Khambhati Emily T. Wang Marina Vannucci Edward F. Chang Vikram R. Rao
+	Bayesian statistics and modelling	2021	Rens van de Schoot Sarah Depaoli Ruth King Bianca Kramer Kaspar Märtens Mahlet G. Tadesse Marina Vannucci Andrew Gelman Duco Veen Joukje E. Willemsen
+	Semiparametric Bayesian Inference for Local Extrema of Functions in the Presence of Noise	2021	Meng Li Zejian Liu Cheng-Han Yu Marina Vannucci
+ PDF Chat	A Bayesian time-varying effect model for behavioral mHealth data	2020	Matthew D. Koslovsky Emily T. Hébert Michael S. Businelle Marina Vannucci
+	Latent Network Estimation and Variable Selection for Compositional Data via Variational EM.	2020	Nathan Osborne Christine B. Peterson Marina Vannucci
+	A Bayesian Time-Varying Effect Model for Behavioral mHealth Data	2020	Matthew D. Koslovsky Emily T. Hébert Michael S. Businelle Marina Vannucci
+ PDF Chat	A Bayesian model of microbiome data for simultaneous identification of covariate associations and prediction of phenotypic outcomes	2020	Matthew D. Koslovsky Kristi L. Hoffman Carrie R. Daniel Marina Vannucci
+	Two‐group Poisson‐Dirichlet mixtures for multiple testing	2020	Francesco Denti Michele Guindani Fabrizio Leisen Antonio Lijoi W. Duncan Wadsworth 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
+	A Bayesian model of microbiome data for simultaneous identification of covariate associations and prediction of phenotypic outcomes.	2020	Matthew D. Koslovsky Kristi L. Hoffman Carrie R. Daniel Marina Vannucci
+ PDF Chat	Bayesian modeling of multiple structural connectivity networks during the progression of Alzheimer's disease	2020	Christine B. Peterson Nathan Osborne Francesco C. Stingo Pierrick Bourgeat James D. Doecke Marina Vannucci
+	Scalable Bayesian variable selection regression models for count data	2020	Yinsen Miao Jeong Hwan Kook Yadong Lu Michele Guindani Marina Vannucci
+	Bayesian Inference for Stationary Points in Gaussian Process Regression Models for Event-Related Potentials Analysis	2020	Cheng-Han Yu Meng Li Colin Noe Simon Fischer‐Baum Marina Vannucci
+	Latent Network Estimation and Variable Selection for Compositional Data via Variational EM	2020	Nathan Osborne Christine B. Peterson Marina Vannucci
+	A Bayesian model of microbiome data for simultaneous identification of covariate associations and prediction of phenotypic outcomes	2020	Matthew D. Koslovsky Kristi L. Hoffman Carrie R. Daniel Marina Vannucci
+	Bayesian Inference of Networks Across Multiple Sample Groups and Data Types	2019	Elin Shaddox Christine B. Peterson Francesco C. Stingo Nicola A. Hanania Charmion Cruickshank‐Quinn Katerina Kechris Russell P. Bowler Marina Vannucci
+	Bayesian Modeling of Multiple Structural Connectivity Networks During the Progression of Alzheimer's Disease	2019	Christine B. Peterson Nathan Osborne Francesco C. Stingo Pierrick Bourgeat James D. Doecke Marina Vannucci
+ PDF Chat	Hierarchical Normalized Completely Random Measures for Robust Graphical Modeling	2019	Andrea Cremaschi Raffaele Argiento Katherine Shoemaker Christine B. Peterson Marina Vannucci
+ PDF Chat	Hierarchical Normalized Completely Random Measures to Cluster Grouped Data	2019	Raffaele Argiento Andrea Cremaschi Marina Vannucci
+ PDF Chat	Bayesian inference of networks across multiple sample groups and data types	2018	Elin Shaddox Christine B. Peterson Francesco C. Stingo Nicola A. Hanania Charmion Cruickshank‐Quinn Katerina Kechris Russell P. Bowler Marina Vannucci
+	A Bayesian Nonparametric Spiked Process Prior for Dynamic Model Selection	2018	Alberto Cassese Weixuan Zhu Michele Guindani Marina Vannucci
+ PDF Chat	A Bayesian mixture model for clustering and selection of feature occurrence rates under mean constraints	2017	Qiwei Li Michele Guindani Brian J. Reich Howard D. Bondell Marina Vannucci
+ PDF Chat	Bayesian variable selection for a semi-competing risks model with three hazard functions	2017	Andrew G. Chapple Marina Vannucci Peter F. Thall Steven H. Lin
+ PDF Chat	An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data	2017	W. Duncan Wadsworth Raffaele Argiento Michele Guindani Jessica Galloway-Peña Samuel A. Shelburne Marina Vannucci
+	Some Themes in High-Dimensional Statistics	2016	Arnoldo Frigessi Peter Bühlmann Ingrid K. Glad Sylvia Richardson Marina Vannucci
+ PDF Chat	A Bayesian Nonparametric Approach for Functional Data Classification with Application to Hepatic Tissue Characterization	2015	Kassandra Fronczyk Michele Guindani Brian P. Hobbs Chaan S. Ng Marina Vannucci
+ PDF Chat	Bayesian models for functional magnetic resonance imaging data analysis	2014	Linlin Zhang Michele Guindani Marina Vannucci
+ PDF Chat	A Bayesian nonparametric approach for the analysis of multiple categorical item responses	2014	Andrew E. Waters Kassandra Fronczyk Michele Guindani Richard G. Baraniuk Marina Vannucci
+ PDF Chat	A spatio-temporal nonparametric Bayesian variable selection model of fMRI data for clustering correlated time courses	2014	Linlin Zhang Michele Guindani Francesco Versace Marina Vannucci
+ PDF Chat	Bayesian Inference of Multiple Gaussian Graphical Models	2014	Christine B. Peterson Francesco C. Stingo Marina Vannucci
+	A hierarchical Bayesian model for inference of copy number variants and their association to gene expression	2014	Alberto Cassese Michele Guindani Mahlet G. Tadesse Francesco Falciani Marina Vannucci
+ PDF Chat	Regularized partial least squares with an application to NMR spectroscopy	2012	Genevera I. Allen Christine B. Peterson Marina Vannucci Mirjana Maletić‐Savatić
+	Order test for high-dimensional two-sample means	2012	Sang H. Lee Johan Lim Erning Li Marina Vannucci Eva Petkova
+	Regularized Partial Least Squares with an Application to NMR Spectroscopy	2012	Genevera I. Allen Christine B. Peterson Marina Vannucci Mirjana Maletić‐Savatić
+ PDF Chat	Incorporating biological information into linear models: A Bayesian approach to the selection of pathways and genes	2011	Francesco C. Stingo Y. Ann Chen Mahlet G. Tadesse Marina Vannucci
+ PDF Chat	An efficient stochastic search for Bayesian variable selection with high-dimensional correlated predictors	2011	Deukwoo Kwon Maria Teresa Landi Marina Vannucci Haleem J. Issaq DaRue A. Prieto Ruth M. Pfeiffer
+ PDF Chat	Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies	2011	Terrance D. Savitsky Marina Vannucci Naijun Sha
+ PDF Chat	A Bayesian graphical modeling approach to microRNA regulatory network inference	2010	Francesco C. Stingo Y. Ann Chen Marina Vannucci Marianne Barrier Philip E. Mirkes
+	Gene Selection for the Identiﬁcation of Biomarkers in High- Throughput Data	2010	Jaesik Jeong Marina Vannucci Kim‐Anh Do Bradley M. Broom Sinae Kim Naijun Sha Mahlet G. Tadesse Kai Yan Lajos Pusztai
+ PDF Chat	A Dirichlet process mixture of hidden Markov models for protein structure prediction	2010	Kristin P. Lennox David B. Dahl Marina Vannucci Ryan Day Jerry Tsai
+ PDF Chat	Spiked Dirichlet Process Priors for Gaussian Process Models	2010	Terrance D. Savitsky Marina Vannucci
+ PDF Chat	Spiked Dirichlet process prior for Bayesian multiple hypothesis testing in random effects models	2009	David B. Dahl Sinae Kim Marina Vannucci
+ PDF Chat	A Bayesian Hierarchical Model for Classification with Selection of Functional Predictors	2009	Hongxiao Zhu Marina Vannucci Dennis D. Cox
+	WAVELET-BASED BAYESIAN ESTIMATION OF PARTIALLY LINEAR REGRESSION MODELSWITH LONG MEMORY ERRORS.	2009	Kyungduk Ko Leming Qu Marina Vannucci
+	Simultaneous inference for multiple testing and clustering via a Dirichlet process mixture model	2008	David B. Dahl Qianxing Mo Marina Vannucci
+ PDF Chat	Bayesian Wavelet-Based Methods for the Detection of Multiple Changes of the Long Memory Parameter	2006	K. Ko Marina Vannucci
+ PDF Chat	Bayesian Methods for Wavelet Series in Single-Index Models	2005	Chun Gun Park Marina Vannucci Jeffrey D. Hart
+ PDF Chat	Wavelet Thresholding with Bayesian False Discovery Rate Control	2005	Mahlet G. Tadesse Joseph G. Ibrahim Marina Vannucci Robert Gentleman
+	Bayesian Variable Selection in Multinomial Probit Models to Identify Molecular Signatures of Disease Stage	2004	Naijun Sha Marina Vannucci Mahlet G. Tadesse Philip J. Brown I. Dragoni Nick Davies Tracy C. Roberts Andrea Contestabile Mike Salmon Christopher D. Buckley
+	Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis	2003	Jeffrey S. Morris Marina Vannucci Philip J. Brown Raymond J. Carroll
+	Rejoinder to "“Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis.”	2003	Jeffrey S. Morris Marina Vannucci Philip J. Brown Raymond J. Carroll
+	A decision theoretical approach to wavelet regression on curves with a high number of regressors	2002	Marina Vannucci Philip J. Brown Tom Fearn
+ PDF Chat	Bayes Model Averaging with Selection of Regressors	2002	Philip J. Brown Marina Vannucci Tom Fearn
+	Predictor Selection for Model Averaging	2001	Marina Vannucci Philip J. Brown Tom Fearn
+	Matlab Code for Bayesian Variable Selection	2000	Marina Vannucci
+ PDF Chat	Covariance Structure of Wavelet Coefficients: Theory and Models in a Bayesian Perspective	1999	Marina Vannucci Fabio Corradi
+	The choice of variables in multivariate regression: a non-conjugate Bayesian decision theory approach	1999	Philip J. Brown Tom Fearn Marina Vannucci
+	Bayesian wavelength selection in multicomponent analysis	1998	Philip J. Brown Marina Vannucci Tom Fearn
+ PDF Chat	Bayesian wavelength selection in multicomponent analysis	1998	Philip J. Brown Marina Vannucci Tom Fearn

Common Coauthors

Coauthor	Papers Together
Michele Guindani	19
Christine B. Peterson	15
Meng Li	9
Philip J. Brown	9
Matthew D. Koslovsky	9
Mahlet G. Tadesse	7
Nathan Osborne	7
Francesco C. Stingo	7
Tom Fearn	6
Cheng-Han Yu	6
Emily T. Hébert	4
Yangfan Ren	4
Beniamino Hadj-Amar	3
Sharon Chiang	3
Suprateek Kundu	3
Kristi L. Hoffman	3
Megan A. K. Peters	3
Michael S. Businelle	3
David B. Dahl	3
Emily T. Wang	3
Jaylen Lee	3
Naijun Sha	3
Raffaele Argiento	3
Linda Ewing‐Cobbs	3
Carrie R. Daniel	3
Dana DeMaster	3
Ryan Warnick	2
Mirjana Maletić‐Savatić	2
Katerina Kechris	2
Jeong Hwan Kook	2
Alberto Cassese	2
Nicola A. Hanania	2
Zijian Zeng	2
Pierrick Bourgeat	2
Isaac Menchaca	2
Jingyan Fu	2
Simon Fischer‐Baum	2
Andreas M. Neophytou	2
Russell P. Bowler	2
Charmion Cruickshank‐Quinn	2
Andrea Cremaschi	2
Chunshan Liu	2
Mingrui Liang	2
Vikram R. Rao	2
James D. Doecke	2
Colin Noe	2
Jack Jewson	2
Xiaoping Hu	2
Elin Shaddox	2
Aaron R. Seitz	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	APPROACHES FOR BAYESIAN VARIABLE SELECTION	1997	Edward I. George Robert E. McCulloch	26
+	Variable Selection via Gibbs Sampling	1993	Edward I. George Robert E. McCulloch	15
+ PDF Chat	Optimal predictive model selection	2004	Maria Maddalena Barbieri James O. Berger	13
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	10
+ PDF Chat	Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables	2013	Nicholas G. Polson James G. Scott Jesse Windle	10
+	Bayesian Density Estimation and Inference Using Mixtures	1995	Michael Escobar Mike West	10
+	Bayesian Analysis of Binary and Polychotomous Response Data	1993	James H. Albert Siddhartha Chib	10
+	Bayesian Variable Selection in Multinomial Probit Models to Identify Molecular Signatures of Disease Stage	2004	Naijun Sha Marina Vannucci Mahlet G. Tadesse Philip J. Brown I. Dragoni Nick Davies Tracy C. Roberts Andrea Contestabile Mike Salmon Christopher D. Buckley	10
+ PDF Chat	A Bayesian Analysis of Some Nonparametric Problems	1973	Thomas S. Ferguson	9
+	Bayesian wavelength selection in multicomponent analysis	1998	Philip J. Brown Marina Vannucci Tom Fearn	9
+ PDF Chat	A Bayesian graphical modeling approach to microRNA regulatory network inference	2010	Francesco C. Stingo Y. Ann Chen Marina Vannucci Marianne Barrier Philip E. Mirkes	9
+ PDF Chat	Inference from Iterative Simulation Using Multiple Sequences	1992	Andrew Gelman Donald B. Rubin	8
+ PDF Chat	Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies	2011	Terrance D. Savitsky Marina Vannucci Naijun Sha	8
+	Sparse inverse covariance estimation with the graphical lasso	2007	Jerome H. Friedman Trevor Hastie R. Tibshirani	8
+ PDF Chat	Scaling It Up: Stochastic Search Structure Learning in Graphical Models	2015	Hao Wang	8
+	Markov Chain Sampling Methods for Dirichlet Process Mixture Models	2000	Radford M. Neal	7
+ PDF Chat	Spiked Dirichlet process prior for Bayesian multiple hypothesis testing in random effects models	2009	David B. Dahl Sinae Kim Marina Vannucci	7
+ PDF Chat	Bayesian Graphical Lasso Models and Efficient Posterior Computation	2012	Hao Wang	7
+	Some matrix-variate distribution theory: Notational considerations and a Bayesian application	1981	A. P. Dawid	7
+	Reversible jump Markov chain Monte Carlo computation and Bayesian model determination	1995	Peter J. Green	7
+	Model selection and estimation in the Gaussian graphical model	2007	Ming Yuan Yi Lin	6
+	Measurement, Regression, and Calibration	1996	Leon Jay Gleser Philip J. Brown	6
+ PDF Chat	A theory for multiresolution signal decomposition: the wavelet representation	1989	Stéphane Mallat	6
+	Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments	1991	John Geweke	6
+ PDF Chat	Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems	1974	C. Antoniak	6
+ PDF Chat	An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data	2017	W. Duncan Wadsworth Raffaele Argiento Michele Guindani Jessica Galloway-Peña Samuel A. Shelburne Marina Vannucci	6
+ PDF Chat	Bayesian Variable Selection in Structured High-Dimensional Covariate Spaces With Applications in Genomics	2010	Fan Li Nancy R. Zhang	6
+	Fundamentals of Nonparametric Bayesian Inference	2017	Subhashis Ghosal Aad van der Vaart	6
+	Bayesian Variable Selection in Linear Regression	1988	Toby J. Mitchell John J. Beauchamp	6
+	Hyper Inverse Wishart Distribution for Non‐decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models	2002	Alberto Roverato	6
+	Multiple shrinkage and subset selection in wavelets	1998	Merlise A. Clyde	5
+ PDF Chat	Wavelet Thresholding via A Bayesian Approach	1998	Felix Abramovich Theofanis Sapatinas B. W. Silverman	5
+ PDF Chat	Scalable Variational Inference for Bayesian Variable Selection in Regression, and Its Accuracy in Genetic Association Studies	2012	Peter Carbonetto Matthew Stephens	5
+	Bayes Factors	1995	Robert E. Kass Adrian E. Raftery	5
+ PDF Chat	Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments	1992	John Geweke	5
+	Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis	2013	Jun Chen Hongzhe Li	5
+ PDF Chat	Bayesian Inference of Multiple Gaussian Graphical Models	2014	Christine B. Peterson Francesco C. Stingo Marina Vannucci	5
+ PDF Chat	Estimating the Dimension of a Model	1978	Gideon Schwarz	5
+	Bayesian Models for Sparse Regression Analysis of High Dimensional Data*	2011	Sylvia Richardson Leonardo Bottolo Jeffrey S. Rosenthal	5
+	High-dimensional graphs and variable selection with the Lasso	2006	Nicolai Meinshausen Peter Bühlmann	5
+	Spatial Bayesian Variable Selection With Application to Functional Magnetic Resonance Imaging	2007	Michael S. Smith Ludwig Fahrmeir	4
+ PDF Chat	Bayes Model Averaging with Selection of Regressors	2002	Philip J. Brown Marina Vannucci Tom Fearn	4
+ PDF Chat	Covariance Structure of Wavelet Coefficients: Theory and Models in a Bayesian Perspective	1999	Marina Vannucci Fabio Corradi	4
+	Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties	2001	Jianqing Fan Runze Li	4
+	The Bayesian Lasso	2008	Trevor Park George Casella	4
+	Monte Carlo sampling methods using Markov chains and their applications	1970	W. Keith Hastings	4
+	Ideal spatial adaptation by wavelet shrinkage	1994	David L. Donoho Iain M. Johnstone	4
+	EMVS: The EM Approach to Bayesian Variable Selection	2013	Veronika Ročková Edward I. George	4
+	Posterior Analysis for Normalized Random Measures with Independent Increments	2008	Lancelot F. James Antonio Lijoi Igor Prünster	4
+	Bayesian auxiliary variable models for binary and multinomial regression	2006	Leonhard Held Chris Holmes	4