2 papers
stat.ME2025
Revisiting Penalized Likelihood Estimation for Deterministic Computer Experiments
Ayumi Mutoh, Annie S. Booth, Jonathan W. Stallrich
Gaussian processes (GPs) are popular as nonlinear regression models for expensive computer simulations, yet GP performance relies heavily on estimation of unknown covariance parame…
stat.CO2025
Influence of Prior Distributions on Gaussian Process Hyperparameter Inference
Ayumi Mutoh, Junoh Heo
Gaussian processes (GPs) are widely used metamodels for approximating expensive computer simulations, particularly in engineering design and spatial prediction. However, their perf…