ChihLi

functional-input-GP

This instruction aims to reproduce the results in the paper “Functional-Input Gaussian Processes with Applications to Inverse Scattering Problems” proposed by Sung, Wang, Cakoni, Harris, and Hung.

GPcluster

This R package allows the estimation and prediction for a clustered Gaussian process model proposed by Sung, Haaland, Hwang, and Lu (2023) in Statistica Sinica

InjectorEmulation

The codes implement the method proposed by Mak, S. et al. (2018) in Journal of the American Statistical Association

mcGP

This R package allows the emulation using a mesh-clustered Gaussian process (mcGP) model for partial differential equation (PDE) systems.

mcGP-Reproducibility

This instruction aims to reproduce the results in the paper “Mesh-clustered Gaussian process emulator for partial differential equation boundary value problems”(2024) to appear in Technometrics.

StackingDesign-Reproducibility

This instruction aims to reproduce the results in the paper “Stacking designs: designing multifidelity computer experiments with target predictive accuracy” by Sung, Ji, Mak, Wang, and Tang (2024) JUQ.

chihli.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

ctGP

Epidemic-Models-Calibration

This instruction aims to reproduce the results in the paper “Efficient calibration for imperfect epidemic models with applications to the analysis of COVID-19” accepted in the Journal of the Royal Statistical Society: Series C

HetCalibrate

This R package allows calibration parameter estimation for inexact computer models with heteroscedastic errors proposed by Sung, Barber, and Walker (2022) in SIAM/ASA Journal on Uncertainty Quantification.

HetCalibrate-Reproducibility

This instruction aims to reproduce the results in the paper “Calibration of inexact computer models with heteroscedastic errors” proposed by Sung, Barber, and Walker (2022).

Understanding-Impact-of-weather-and-intervention-on-COVID-19-AoAs

This instruction aims to reproduce the results in the paper “Estimating functional parameters for understanding the impact of weather and government interventions on COVID-19 outbreak” published in the Annals of Applied Statistics 2022