104 citations · 248 across the 7 of their papers we have counts for
7 papers
A Case Study in Model Failure? COVID-19 Daily Deaths and ICU Bed Utilisation Predictions in New York State
Vincent Chin, Noelle I. Samia, Roman Marchant +4
Forecasting models have been influential in shaping decision-making in the COVID-19 pandemic. However, there is concern that their predictions may have been misleading. Here, we di…
Learning as We Go: An Examination of the Statistical Accuracy of COVID19 Daily Death Count Predictions
Roman Marchant, Noelle I. Samia, Ori Rosen +2
This paper provides a formal evaluation of the predictive performance of a model (and its various updates) developed by the Institute for Health Metrics and Evaluation (IHME) for p…
Ecological Regression with Partial Identification
Wenxin Jiang, Gary King, Allen Schmaltz +1
Ecological inference (EI) is the process of learning about individual behavior from aggregate data. We study a partially identified linear contextual effects model for EI and descr…
Hierarchical Mixtures-of-Experts for Exponential Family Regression Models with Generalized Linear Mean Functions: A Survey of Approximation and Consistency Results
Wenxin Jiang, Martin A. Tanner
We investigate a class of hierarchical mixtures-of-experts (HME) models where exponential family regression models with generalized linear mean functions of the form psi(ga+fx^Tfgb…
From EM to Data Augmentation: The Emergence of MCMC Bayesian Computation in the 1980s
Martin A. Tanner, Wing H. Wong
It was known from Metropolis et al. [J. Chem. Phys. 21 (1953) 1087--1092] that one can sample from a distribution by performing Monte Carlo simulation from a Markov chain whose equ…
Gibbs posterior for variable selection in high-dimensional classification and data mining
Wenxin Jiang, Martin A. Tanner
In the popular approach of "Bayesian variable selection" (BVS), one uses prior and posterior distributions to select a subset of candidate variables to enter the model. A completel…