activity
20062026
most citedMarkov Chain Monte Carlo: Can We Trust the Third Significant Figure?

275 citations · 410 across the 25 of their papers we have counts for

collaborators

30 papers

stat.AP2026

Estimating water levels in the High Plains Aquifer by synthesizing satellite data with groundwater well observations

Anis Pakrashi, Murali Haran, Shan Zuidema

The High Plains Aquifer (HPA) is a critical water resource in the Central United States, yet its depletion remains a major concern. While the Gravity Recovery and Climate Experimen…

stat.ME2025

Probabilistic Downscaling for Flood Hazard Models

Samantha Roth, Sanjib Sharma, Atieh Alipour +2

Riverine flooding poses significant risks. Developing strategies to manage flood risks requires flood projections with decision-relevant scales and well-characterized uncertainties…

stat.ME2023

A Class of Models for Large Zero-inflated Spatial Data

Ben Seiyon Lee, Murali Haran

Spatially correlated data with an excess of zeros, usually referred to as zero-inflated spatial data, arise in many disciplines. Examples include count data, for instance, abundanc…

stat.ME2023

A Shared Component Point Process Model for Urban Policing

Claire Kelling, Murali Haran

Newly available point-level datasets allow us to relate police use of force to other events describing police behavior. Current methods for relating two point processes typically r…

stat.ME2022

Flood hazard model calibration using multiresolution model output

Samantha Roth, Ben Seiyon Lee, Sanjib Sharma +3

Riverine floods pose a considerable risk to many communities. Improving flood hazard projections has the potential to inform the design and implementation of flood risk management…

stat.ME2021★ 2 cited

A Two-Stage Cox Process Model with Spatial and Nonspatial Covariates

Claire Kelling, Murali Haran

Rich new marked point process data allow researchers to consider disparate problems such as the factors affecting the location and type of police use of force incidents, and the ch…