• Publications
  • Influence
Regression-Based Inverse Distance Weighting With Applications to Computer Experiments
TLDR
Inverse distance weighting (IDW) is a simple method for multivariate interpolation but has poor prediction accuracy. Expand
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Comparing the Slack-Variable Mixture Model With Other Alternatives
TLDR
We advocate that for some mixture experiments the slack-variable model has appealing properties including numerical stability and better prediction accuracy when model-term selection is performed. Expand
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  • 2
Bayesian Optimal Single Arrays for Robust Parameter Design
TLDR
We propose a Bayesian approach to develop single arrays which incorporate the importance of control-by-noise interactions in robust parameter design without altering the effect hierarchy. Expand
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Design and Modeling Strategies for Mixture-of-Mixtures Experiments
TLDR
We propose a new model called the major–minor model to overcome some of the limitations of the commonly used multiple-Scheffé model. Expand
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D-optimal Design for Network A/B Testing
TLDR
In this paper, we propose to use the conditional auto-regressive model to present the network structure and include the network effects in the estimation and inference of the treatment effect. Expand
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Product defect rate confidence bound with attribute and variable data
TLDR
We provide a bootstrap methodology to construct a (1−α)100% upper confidence bound for the overall defect rate of a product whose quality assessment involves multiple pass/fail binary data and multiple continuous data. Expand
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Bayesian optimal blocking of factorial designs
The presence of block effects makes the optimal selection of fractional factorial designs a difficult task. The existing frequentist methods try to combine treatment and block wordlength patterns andExpand
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Kernel Approximation: From Regression to Interpolation
  • Lulu Kang, V. Joseph
  • Mathematics, Computer Science
  • SIAM/ASA J. Uncertain. Quantification
  • 16 February 2016
TLDR
We introduce a new interpolation method, known as kernel interpolation (KI), for modeling the output from expensive deterministic computer experiments. Expand
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Additive Heredity Model for the Analysis of Mixture-of-Mixtures Experiments
TLDR
We propose an additive heredity model (AHM) for analyzing MoM experiments. Expand
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