“Computationally Efficient Bayesian Unit-Level Modeling of Non-Gaussian Survey Data under Informative Sampling,” presented by Paul A. Parker, Assistant Professor, Department of Statistics, University of California Santa Cruz
Events
NYC Open Data Case Studies from Introduction to Data Science at UConn
The STAT 5255/3255 class (Introduction to Data Science) is scheduled to present to the public on March 8, at 3:30 pm ET, as part of the NYC Open Data Week event. There will be four group presentations on two NYC Open data sets: NYC motor vehicle collisions and NYC Department of Buildings job applications.
Paper of the Month: March 2022
Chib, S., (1995). Marginal Likelihood From the Gibbs Output. Journal of the American Statistical Association, 90, 1313-1321.
Statistics Colloquium: Simon Mak, Duke University
“A Graphical Multi-Fidelity Gaussian Process Model, With Application to Emulation of Expensive Computer Simulations,” presented by Simon Mak, Assistant Professor, Department of Statistical Science, Duke University
Statistics Colloquium: Jian Huang, University of Iowa
“A Deep Generative Approach to Learning a Conditional Distribution,” presented by Jian Huang, Professor, Department of Statistics and Actuarial Science, Department of Biostatistics, University of Iowa
Statistics Colloquium: Jyotishka Datta, Virginia Tech
New Directions in Bayesian Shrinkage for Sparse, Structured Data,” presented by Jyotishka Datta, Assistant Professor, Department of Statistics, Virginia Tech
Paper of the Month: February 2022
Nozer D. Singpurwalla, Nicholas G. Polson & Refik Soyer (2018), From Least Squares to Signal Processing and Particle Filtering, Technometrics, 60:2, 146-160.
Interdisciplinary Seminar: Andrew Ho, Harvard University
“Test Validation for a Crisis: Five Practical Heuristics for the Best and Worst of Times,” presented by Dr. Andrew Ho, Harvard University
Statistics Colloquium: Neil Spencer, Harvard School of Public Health
“Fast Approximate BayesBag Model Selection via Taylor Expansions,” presented by Neil Spencer, Postdoctoral Researcher, Department of Biostatistics, Harvard School of Public Health
Statistics Colloquium: Aaron Schein, Columbia University
“Complex Structure Discovery and Randomized Field Experiments on Large-Scale Social and Political Networks,” presented by Aaron Schein, Postdoctoral Fellow, Data Science Institute, Columbia University