marinavannucci

snbvbs

Code for "Scalable Bayesian Variable Selection Regression Models for Count Data", by Miao et al. (2019), in Flexible Bayesian Regression Modelling, Yanan F. et al (Eds), Elsevier, 187-219.

NPBayes_fMRI

User friendly MATLAB GUI for Bayesian nonparametric spatio-temporal modeling of fMRI data. Accompany paper: Kook et al. (2019). NPBayes-fMRI: Nonparametric Bayesian General Linear Models for Single- and Multi-Subject fMRI Data. Statistics in Biosciences, 11(1), 3-21.

Bayesian-tensor-modeling

Functions to implement Bayesian Tensor Modeling (BT-SVM and BT-LR) in R

BayesRPAGP

Random Phase-Amplitude Gaussian Process

BIoS_SGLSS

Code for "Bayesian Image-on-Scalar Regression with a Spatial Global-Local Spike-and-Slab Prior" (BA, 2022+)

BVAR_connect

Bayesian multi-subject vector autoregressive (VAR) model for inference on effective brain connectivity based on resting-state functional MRI data. Kook et al. (2021), Neuroinformatics, 19, 39-56.

ClusteringFunctionalTrajectoriesOverTime

Associated files for Liang, M., Koslovsky, M.D., Hebert, E.T., Kendzor, D.E., and Vannucci, M. (2024+) A Bayesian Nonparametric Approach for Clustering Functional Trajectories over Time

DGP-MCEM

R code for Monte Carlo EM algorithm of derivative Gaussian process model - Yu et al. (2022, Biometrics)

DGP-theory

Code for reproducing results of simulated data sets of sample size 100 in the paper "Semiparametric Bayesian inference for local extrema of functions in the presence of noise"

dmbvs

R/C code for Bayesian variable selection for Dirichlet-multinomial regression models. Accompany paper: Wadsworth et al. (2016). An Integrative Bayesian Dirichlet-Multinomial Regression Model for the Analysis of Taxonomic Abundances in Microbiome data. BMC Bioinformatics 18:94.

DMLMbvs

A Bayesian model of microbiome data for simultaneous identification of covariate associations and prediction of phenotypic outcomes - Koslovsky et al. (2020), Annals of Applied Stats, 14(3), 1471-1492.

dynamic-and-robust-Bayesian-graphical-models

HMMbvs

Software for paper Liang, M. et al (2021). Bayesian Continuous-Time Hidden Markov Models with Covariate Selection for Intensive Longitudinal Data with Measurement Error. Psychological Methods, in press.

Linked_precision_matrices

MCMC and simulation code for "Bayesian Modeling of Multiple Structural Connectivity Networks During the Progression of Alzheimer’s Disease"

MicroBVS

Software for the paper Koslovsky, M.D. and Vannucci, M. (2020). MicroBVS: Dirichlet-Tree Multinomial Regression Models with Bayesian Variable Selection – an R package. BMC Bioinformatics, 21:301.

multiGGM

Bayesian inference of multiple Gaussian graphical models

mvHMM

Bayesian Multivariate HMM

Negative-binomial-dynamic-linear-model

This code implements a negative binomial dynamic linear model for count data. To access code: Please submit requests to seizurerisk@gmail.com.

PGBVS

Software for the paper Koslovsky, M.D., Hebert, E.T., Businelle, M.S. and Vannucci, M. (2020). A Bayesian Time-Varying Effect Model for Behavioral mHealth Data. Annals of Applied Statistics, 14(4), 1878-1902.

PIBDFC

This is a repository for the Matlab implementation of the Predictor-Informed Dynamic Functional Connectivity model of Lee et al.

RVS

SINC

SINC Algorithm from the paper Osborne, N., Peterson, C.B. and Vannucci, M. (2021), "Latent Network Estimation and Variable Selection for Compositional Data via Variational EM", JCGS.

slam

R code for Monte Carlo EM algorithm of Semiparametric Latent ANOVA Model (SLAM)

sparseVARHSMM

sparse VAR approximate HSMM

Statistics-Epilepsy-Book

Statistical Methods in Epilepsy

Switching-linear-dynamical-system-with-variable-selection

This code implements a switching linear dynamical system with variable selection for estimation of latent states from count data. To access code: Please submit requests to seizurerisk@gmail.com.

VBMultDirReg

Variational Bayes for Dirichlet-Multinomial Regression. Code for "Scalable Bayesian Variable Selection Regression Models for Count Data", by Miao et al. (2019), in Flexible Bayesian Regression Modelling, Yanan F. et al (Eds), Elsevier, 187-219.

VEVAR-fmri

Zero-inflated-negative-binomial-nonhomogeneous-hidden-Markov-model-with-variable-selection

Zero-inflated negative binomial non-homogeneous hidden Markov model with variable selection for seizure risk: Wang ET, Chiang S, Haneef Z, Rao VR, Moss R, Vannucci M. Bayesian non-homogeneous hidden Markov model with variable selection for investigating drivers of seizure risk cycling. Annals of Applied Statistics, 2022 (in press).

Zero-inflated-Poisson-nonhomogeneous-hidden-Markov-model

Zero inflated Poisson non-homogeneous hidden Markov model for seizure risk: Chiang S, Vannucci M, Goldenholz DM, Moss R, Stern JM. Epilepsy as a dynamic disease: A Bayesian model for differentiating seizure risk from natural variability. Epilepsia Open. 2018 Apr 20;3(2):236-246.