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stat.ME2026
Bayesian Nonparametric Approaches to Ordinal Drought Modeling in the United States
Mostafa Shams, Robert Erhardt, Staci Hepler
Data observed over space and time can exhibit dependence across both dimensions, and datasets can grow very large in both the number of locations and the number of time periods. Th…
stat.ME2026
Three Case Studies of Two-stage MCMC for Fast Bayesian Inference of Large Spatio-temporal Data
Mostafa Shams, Robert Erhardt, Staci Hepler
High dimensional spatio-temporal models can quickly run up against computational limitations. Recursive or multi-stage Bayesian algorithms are one way to address this computational…
stat.ME2023
Modeling Insurance Claims using Bayesian Nonparametric Regression
Mostafa Shams Esfand Abadi, Kaushik Ghosh
The prediction of future insurance claims based on observed risk factors, or covariates, help the actuary set insurance premiums. Typically, actuaries use parametric regression mod…