3 papers
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.AP2026
The Impact of a Gridded Streamflow Measure on Drought Variation in the Conterminous United States
Rob Erhardt, Courtney Di Vittorio, Staci Hepler +3
Models for droughts draw on a wide range of meteorological and hydrological inputs. Stakeholders classify droughts according to different purposes and priorities, and accordingly r…
stat.ME2025
Two-stage MCMC for Fast Bayesian Inference of Large Spatio-temporal Ordinal Data, with Application to US Drought
Staci Hepler, Rob Erhardt
High dimensional space-time data pose known computational challenges when fitting spatio-temporal models. Such data show dependence across several dimensions of space as well as in…