A weighted D-optimality criterion for constructing model-robust designs in the presence of block effects
It is generally known that blocking can reduce unexplained variation, and in response surface designs block sizes can be pre-specified. This paper proposes a novel way of weighting D-optimality criteria obtained from all possible models to construct robust designs with blocking factors and address...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Prince of Songkla University
2020-12-01
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| Series: | Songklanakarin Journal of Science and Technology (SJST) |
| Subjects: | |
| Online Access: | https://rdo.psu.ac.th/sjstweb/journal/42-6/13.pdf |
| _version_ | 1818119098505101312 |
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| author | Peang-or Yeesa Patchanok Srisuradetchai John J. Borkowski |
| author_facet | Peang-or Yeesa Patchanok Srisuradetchai John J. Borkowski |
| author_sort | Peang-or Yeesa |
| collection | DOAJ |
| description | It is generally known that blocking can reduce unexplained variation, and in response surface designs block sizes can
be pre-specified. This paper proposes a novel way of weighting D-optimality criteria obtained from all possible models to
construct robust designs with blocking factors and addresses the challenge of uncertainty as to whether a first-order model, an
interaction model, or a second-order model is the most appropriate choice. Weighted D-optimal designs having 2 and 3 variables
with 2, 3, and 4 blocks are compared with corresponding standard D-optimal designs in terms of the
DN
-efficiencies. Effects of
blocking schemes are also investigated. Both an exchange algorithm (EA) and a genetic algorithm (GA) are employed to generate
the model-robust designs. The results show that the proposed
Dw
-optimality criterion can be a good alternative for researchers as
it can create robust designs across the set of potential models. |
| first_indexed | 2024-12-11T05:04:48Z |
| format | Article |
| id | doaj.art-5e139e4b05fb47889182f034db0e3b64 |
| institution | Directory Open Access Journal |
| issn | 0125-3395 |
| language | English |
| last_indexed | 2024-12-11T05:04:48Z |
| publishDate | 2020-12-01 |
| publisher | Prince of Songkla University |
| record_format | Article |
| series | Songklanakarin Journal of Science and Technology (SJST) |
| spelling | doaj.art-5e139e4b05fb47889182f034db0e3b642022-12-22T01:20:03ZengPrince of Songkla UniversitySongklanakarin Journal of Science and Technology (SJST)0125-33952020-12-014261259127310.14456/sjst-psu.2020.164A weighted D-optimality criterion for constructing model-robust designs in the presence of block effectsPeang-or Yeesa0Patchanok Srisuradetchai1John J. Borkowski2Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Khlong Luang, Pathum Thani, 12121 ThailandDepartment of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Khlong Luang, Pathum Thani, 12121 ThailandDepartment of Mathematical Sciences, Montana State University, Bozeman, Montana, 59717-2400 United States of AmericaIt is generally known that blocking can reduce unexplained variation, and in response surface designs block sizes can be pre-specified. This paper proposes a novel way of weighting D-optimality criteria obtained from all possible models to construct robust designs with blocking factors and addresses the challenge of uncertainty as to whether a first-order model, an interaction model, or a second-order model is the most appropriate choice. Weighted D-optimal designs having 2 and 3 variables with 2, 3, and 4 blocks are compared with corresponding standard D-optimal designs in terms of the DN -efficiencies. Effects of blocking schemes are also investigated. Both an exchange algorithm (EA) and a genetic algorithm (GA) are employed to generate the model-robust designs. The results show that the proposed Dw -optimality criterion can be a good alternative for researchers as it can create robust designs across the set of potential models.https://rdo.psu.ac.th/sjstweb/journal/42-6/13.pdfexperimental designd-optimalityweak hereditygenetic algorithm |
| spellingShingle | Peang-or Yeesa Patchanok Srisuradetchai John J. Borkowski A weighted D-optimality criterion for constructing model-robust designs in the presence of block effects Songklanakarin Journal of Science and Technology (SJST) experimental design d-optimality weak heredity genetic algorithm |
| title | A weighted D-optimality criterion for constructing model-robust designs in the presence of block effects |
| title_full | A weighted D-optimality criterion for constructing model-robust designs in the presence of block effects |
| title_fullStr | A weighted D-optimality criterion for constructing model-robust designs in the presence of block effects |
| title_full_unstemmed | A weighted D-optimality criterion for constructing model-robust designs in the presence of block effects |
| title_short | A weighted D-optimality criterion for constructing model-robust designs in the presence of block effects |
| title_sort | weighted d optimality criterion for constructing model robust designs in the presence of block effects |
| topic | experimental design d-optimality weak heredity genetic algorithm |
| url | https://rdo.psu.ac.th/sjstweb/journal/42-6/13.pdf |
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