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20172026
most citedAdjustments to Computer Models via Projected Kernel Calibration

4 citations · 9 across the 16 of their papers we have counts for

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5 papers · 1 filter

stat.ME2026

Statistical Validation of Computer Models: Global and Subdomain Hypothesis Testing

Chaoan Li, Xianyang Zhang, Rui Tuo

Computer simulations play an important role in scientific discovery and engineering innovation. Reliable computer models enable virtual experimentation that reduces the need for co…

stat.ME2024

Fixed-budget optimal designs for multi-fidelity computer experiments

Gecheng Chen, Rui Tuo

This work focuses on the design of experiments of multi-fidelity computer experiments. We consider the autoregressive Gaussian process model proposed by Kennedy and O'Hagan (2000)…

stat.ME2022

Hypothesis Tests with Functional Data for Surface Quality Change Detection in Surface Finishing Processes

Shilan Jin, Rui Tuo, Akash Tiwari +5

This work is concerned with providing a principled decision process for stopping or tool-changing in a surface finishing process. The decision process is supposed to work for produ…

stat.ME2021

A Reproducing Kernel Hilbert Space Approach to Functional Calibration of Computer Models

Rui Tuo, Shiyuan He, Arash Pourhabib +2

This paper develops a frequentist solution to the functional calibration problem, where the value of a calibration parameter in a computer model is allowed to vary with the value o…

stat.ME20174 cited

Adjustments to Computer Models via Projected Kernel Calibration

Rui Tuo

Identification of model parameters in computer simulations is an important topic in computer experiments. We propose a new method, called the projected kernel calibration method, t…