168 citations · 768 across the 62 of their papers we have counts for
67 papers
Bivariate DeepKriging for Large-scale Spatial Interpolation of Wind Fields
Pratik Nag, Ying Sun, Brian J Reich
High spatial resolution wind data are essential for a wide range of applications in climate, oceanographic and meteorological studies. Large-scale spatial interpolation or downscal…
Spatio-temporal DeepKriging for Interpolation and Probabilistic Forecasting
Pratik Nag, Ying Sun, Brian J Reich
Gaussian processes (GP) and Kriging are widely used in traditional spatio-temporal mod-elling and prediction. These techniques typically presuppose that the data are observed from…
A Deep Learning Synthetic Likelihood Approximation of a Non-stationary Spatial Model for Extreme Streamflow Forecasting
Reetam Majumder, Brian Reich
Extreme streamflow is a key indicator of flood risk, and quantifying the changes in its distribution under non-stationary climate conditions is key to mitigating the impact of floo…
A Bayesian Semiparametric Method For Estimating Causal Quantile Effects
Steven G. Xu, Shu Yang, Brian J. Reich
Standard causal inference characterizes treatment effect through averages, but the counterfactual distributions could be different in not only the central tendency but also spread…
SPQR: An R Package for Semi-Parametric Density and Quantile Regression
Steven G. Xu, Reetam Majumder, Brian J. Reich
We develop an R package SPQR that implements the semi-parametric quantile regression (SPQR) method in Xu and Reich (2021). The method begins by fitting a flexible density regressio…
Matching Estimators of Causal Effects in Clustered Observational Studies with Application to Quantifying the Impact of Marine Protected Areas on Biodiversity
Can Cui, Shu Yang, Brian J Reich +1
Marine conservation preserves fish biodiversity, protects marine and coastal ecosystems, and supports climate resilience and adaptation. Despite the importance of establishing mari…