7 papers · 1 filter
Bayesian Gaussian Mixture Modeling for Symmetric Matrix Variate Data
Malcolm Wolff, Adrian Dobra, 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…
Linear Models, Variable Selection, Artificial Intelligence
By Riyadh Alrawkan, Edward Boone, Ryad Ghanam +1
Variable selection in linear regression models has been a problem since hypothesis testing began. Which variables to include or exclude from a model is not an easy task. Techniques…
Bayesian nonparametric modeling of dynamic pollution clusters through an autoregressive logistic-beta Stirling-gamma process
Santiago Marin, Bronwyn Loong, Anton H. Westveld
Fine suspended particulates (FSP), commonly known as PM2.5, are among the most harmful air pollutants, posing serious risks to population health and environmental integrity. As suc…
Model-based calibration of gear-specific fish abundance survey data as a change-of-support problem
Grace S. Chiu, Anton H. Westveld, Mark A. Albins +5
For commercial and recreational fisheries of a wide-ranging species to be sustainable, abundance studies from neighboring regions should be unified. For the first time in the USA,…
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…
Adaptive Shrinkage with a Nonparametric Bayesian Lasso
Santiago Marin, Bronwyn Loong, Anton H. Westveld
Modern approaches to perform Bayesian variable selection rely mostly on the use of shrinkage priors. That said, an ideal shrinkage prior should be adaptive to different signal leve…