R Packages
- RNAmf: Recursive non-additive emulator for multi-fidelity data
- mcGP: Perform the mesh-clustered Gaussian process emulator for partial differential equation boundary value problems
- GPcluster: Perform the clustered Gaussian process model proposed by Sung et al. (2023) Statistica Sinica
- HetCalibrate: Calibration parameter estimation for inexact computer models with heteroscedastic errors
- calibrateBinary: Calibration for computer experiments with binary responses
- binaryGP: Fit and predict a Gaussian process model with (time-series) binary response
- MRFA: Fitting and predicting large-scale nonlinear regression problems using multi-resolution functional ANOVA (MRFA) approach
Reproducibility
- Active learning for a recursive non-additive emulator for multi-fidelity computer experiments
- Category tree Gaussian process for computer experiments with many-category qualitative factors and application to cooling system design (2024+) Journal of Quality Technology
- Mesh-clustered Gaussian process emulator for partial differential equation boundary value problems (2024+) Technometrics
- Stacking designs: designing multifidelity computer experiments with target predictive accuracy (2024) SIAM/ASA Journal on Uncertainty Quantification, 12(1), 157-181.
- Efficient calibration for imperfect epidemic models with applications to the analysis of COVID-19 (2024) Journal of the Royal Statistical Society: Series C, 73(1), 47-64.
- Functional-input Gaussian processes with applications to inverse scattering problems (2024) Statistica Sinica, 34(4)
- Calibration of inexact computer models with heteroscedastic errors (2022). SIAM/ASA Journal on Uncertainty Quantification, 10(4), 1733-1752.
- Estimating functional parameters for understanding the impact of weather and government interventions on COVID-19 outbreak (2022). Annals of Applied Statistics, 16(4), 2505-2522.
- An efficient surrogate model for emulation and physics extraction of large eddy simulations (2018). Journal of the American Statistical Association, 113(524):1443-1456.
