Supersaturated multistratum designs

Lin, Chang-Yun

doi:10.1080/00224065.2018.1507222

Cited by 8 publications

(9 citation statements)

References 35 publications

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“…The coordinate‐exchange algorithm is an efficient algorithm for constructing and searching for optimal designs. It can be easily modified and applied to search for the

\overset{I}{true}

‐optimal and

Ā

‐optimal designs.…”

Section: Algorithm and Approximate Methodsmentioning

confidence: 99%

“…Among these approaches, the Bayesian D , minimax, and compound criteria first specify a minimum model and then consider larger models including additional effects not in the minimum model while the Q B criterion first specifies a maximum model and then considers projective submodels of the maximum model. There also exist several extensions of the D and A criteria, which can be applied to generate multistratum designs . Since these extension approaches do not depend on a single model, designs selected by these criteria are more robust to model uncertainty.…”

Section: Introductionmentioning

confidence: 99%

“…There also exist several extensions of the D and A criteria, which can be applied to generate multistratum designs. [5][6][7] Since these extension approaches do not depend on a single model, designs selected by these criteria are more robust to model uncertainty.…”

Section: Introductionmentioning

confidence: 99%

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Robust designs with high projection efficiency

Lin

2018

Quality & Reliability Eng

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Alphabetic optimality criteria, such as the D, A, and I criteria, require specifying a model to select optimal designs. They are not model‐free, and the designs obtained by them may not be robust. Recently, many extensions of the D and A criteria have been proposed for selecting robust designs with high estimation efficiency. However, approaches for finding robust designs with high prediction efficiency are rarely studied in the literature. In this paper, we propose a compound criterion and apply the coordinate‐exchange 2‐phase local search algorithm to generate robust designs with high estimation, high prediction, or balanced estimation and prediction efficiency for projective submodels. Examples demonstrate that the designs obtained by our method have better projection efficiency than many existing designs.

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“…The coordinate‐exchange algorithm is an efficient algorithm for constructing and searching for optimal designs. It can be easily modified and applied to search for the

\overset{I}{true}

‐optimal and

Ā

‐optimal designs.…”

Section: Algorithm and Approximate Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust designs with high projection efficiency

Lin

2018

Quality & Reliability Eng

Self Cite

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“…It has a 3‐stratum structure. More discussions about staggered‐level designs can be found in Webb et al, Arnouts and Goos, and Lin …”

Section: Applications Comparisons and Sensitivity Analysesmentioning

confidence: 99%

“…However, the Bayesian D criterion proposed by DuMouchel and Jones was developed under the framework of single‐stratum structures and cannot be applied to select designs that have multistratum structures . This motivates us to extend the Bayesian approach for more complicated experiments.…”

Section: Introductionmentioning

confidence: 96%

Generalized BayesianDcriterion for single‐stratum and multistratum designs

Lin

2018

Quality & Reliability Eng

Self Cite

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The Bayesian D criterion modifies the D‐optimality approach to reduce dependence of the selected design on an assumed model. This criterion has been applied to select various single‐stratum designs for completely randomized experiments when the number of effects is greater than the sample size. In many industrial experiments, complete randomization is sometimes expensive or infeasible, and hence, designs used for the experiments often have multistratum structures. However, the original Bayesian D criterion was developed under the framework of single‐stratum structures and cannot be applied to select multistratum designs. In this paper, we study how to extend the Bayesian approach for more complicated experiments and develop the generalized Bayesian D criterion, which generalizes the original Bayesian D criterion and can be applied to select single‐stratum and multistratum designs for various experiments when the number of effects is greater than the rank of the model matrix.

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Data-driven multistratum designs with the generalized BayesianD-Dcriterion for highly uncertain models

Lin

Yang

2019

Computational Statistics & Data Analysis

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Supersaturated multistratum designs

Cited by 8 publications

References 35 publications

Robust designs with high projection efficiency

Robust designs with high projection efficiency

Generalized BayesianDcriterion for single‐stratum and multistratum designs

Data-driven multistratum designs with the generalized BayesianD-Dcriterion for highly uncertain models

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