195 citations · 433 across the 22 of their papers we have counts for
13 papers · 1 filter
Bayesian Gaussian Mixture Modeling for Symmetric Matrix Variate Data
Malcolm Wolff, Grace S. Chiu, Anton H. Westveld +1
Statistical inference on individual activity networks has been a historically difficult task due to the lack of available data at the appropriate granularity and the complexity of…
An Object-Oriented Spatial Statistics Approach for Human Activity Space Estimation
Haoyang Wu, Yen-Chi Chen, Adrian Dobra
Human activity spaces are shaped by individual mobility and the built environment, motivating statistical methods that integrate GPS observations with GIS representations of places…
Estimation of Contextual Exposure to HIV from GPS Data
Haoyang Wu, Zhaoxing Wu, Thulile Mathenjwa +10
We present a comprehensive statistical methodological framework for estimating contextual exposure to HIV that includes local (grid-cell level) estimation of HIV prevalence and hum…
Bayesian Inference for Single-factor Graphical Models
David Marcano, Adrian Dobra
We introduce efficient MCMC algorithms for Bayesian inference for single-factor models with correlated residuals where the residuals' distribution is a Gaussian graphical model. We…
Modeling Human Spatial Mobility Patterns with the Lévy Flight Cluster Model
Malcolm Wolff, Adrian Dobra, Anton H. Westveld +1
Despite the extensive collection of individual mobility data over the past decade, fueled by the widespread use of GPS-enabled personal devices, the existing statistical literature…
A statistical framework for analyzing activity pattern from GPS data
Haoyang Wu, Yen-Chi Chen, Adrian Dobra
We introduce a novel statistical framework for analyzing the GPS data of a single individual. Our approach models daily GPS observations as noisy measurements of an underlying rand…
Bayesian Finite Mixtures of Ising Models
Zhen Miao, Yen-Chi Chen, Adrian Dobra
We introduce finite mixtures of Ising models as a novel approach to study multivariate patterns of associations of binary variables. Our proposed models combine the strengths of Is…
Loglinear model selection and human mobility
Adrian Dobra, Abdolreza Mohammadi
Methods for selecting loglinear models were among Steve Fienberg's research interests since the start of his long and fruitful career. After we dwell upon the string of papers focu…
Graphical Modeling of Spatial Health Data
Adrian Dobra
The literature on Gaussian graphical models (GGMs) contains two equally rich and equally significant domains of research efforts and interests. The first research domain relates to…
Restricted Covariance Priors with Applications in Spatial Statistics
Theresa R. Smith, Jon Wakefield, Adrian Dobra
We present a Bayesian model for area-level count data that uses Gaussian random effects with a novel type of G-Wishart prior on the inverse variance--covariance matrix. Specificall…
Relational models for contingency tables
Anna Klimova, Tamás Rudas, Adrian Dobra
The paper considers general multiplicative models for complete and incomplete contingency tables that generalize log-linear and several other models and are entirely coordinate fre…
Bayesian inference for general Gaussian graphical models with application to multivariate lattice data
Adrian Dobra, Alex Lenkoski, Abel Rodriguez
We introduce efficient Markov chain Monte Carlo methods for inference and model determination in multivariate and matrix-variate Gaussian graphical models. Our framework is based o…
Sparse covariance estimation in heterogeneous samples
Abel Rodriguez, Alex Lenkoski, Adrian Dobra
Standard Gaussian graphical models (GGMs) implicitly assume that the conditional independence among variables is common to all observations in the sample. However, in practice, obs…