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      다중 외삽점에서의 최적 실험설계법을 위한 실험설계기준 = Some Criteria for Optimal Experimental Design at Multiple Extrapolation Points

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      https://www.riss.kr/link?id=A105171805

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      다국어 초록 (Multilingual Abstract)

      When setting up an experiment for extrapolation at multiple points outside the design space, we often face a difficulty in which point we should emphasize even if the polynomial model under consideration is given. In this paper we propose various methods under two possible scenarios that deal with extrapolations. One considered in this paper is the situation when the model assumed can be extended beyond the design space. In this setting, the many classical methods(including various approaches the authors proposed before) were revisited in the context of extrapolation. But the real problem arises when there is an uncertainty concerning the validity of the assumed model. Therefore, the second scenario is to develop an appropriate procedure when we have limited information about model. Consequently, a hybrid approach is suggested to deal with this issue of how to handle the multiple extrapolating under model uncertainty. A search algorithm was implemented because the classical exchange algorithm was found difficult to handle the complexity of the problem.
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      When setting up an experiment for extrapolation at multiple points outside the design space, we often face a difficulty in which point we should emphasize even if the polynomial model under consideration is given. In this paper we propose various meth...

      When setting up an experiment for extrapolation at multiple points outside the design space, we often face a difficulty in which point we should emphasize even if the polynomial model under consideration is given. In this paper we propose various methods under two possible scenarios that deal with extrapolations. One considered in this paper is the situation when the model assumed can be extended beyond the design space. In this setting, the many classical methods(including various approaches the authors proposed before) were revisited in the context of extrapolation. But the real problem arises when there is an uncertainty concerning the validity of the assumed model. Therefore, the second scenario is to develop an appropriate procedure when we have limited information about model. Consequently, a hybrid approach is suggested to deal with this issue of how to handle the multiple extrapolating under model uncertainty. A search algorithm was implemented because the classical exchange algorithm was found difficult to handle the complexity of the problem.

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      참고문헌 (Reference)

      1 김영일, "하이브리드형 제약 외삽실험 계획법" 한국통계학회 19 (19): 65-75, 2012

      2 Limmun, W., "Using a Genetic Algorithm to Generate D-optimal Designs for Mixture Experiments" 29 : 1055-1068, 2013

      3 Dette, H., "Robust optimal extrapolation designs" 83 : 667-680, 1996

      4 Box, G. E. P., "Robust design" 62 : 347-352, 1975

      5 Kiefer, J., "Optimum extrapolation and interpolation designs" 16 : 79-108, 1964

      6 Hoel, P. G., "Optimal spacing and weighting in polynomial prediction" 35 : 1553-1560, 1964

      7 Stigler, S. M., "Optimal experimental design for polynomial regression" 66 : 311-318, 1971

      8 Studden, W. J., "Optimal designs for multivariate polynomial extrapolation" 42 : 828-832, 1971

      9 Cook, R. D., "On the equivalence between constrained and compound optimal designs" 89 : 687-692, 1994

      10 Myung-WookKahng, "Multiple Constrained Optimal Experimental Design" 한국통계학회 9 (9): 4-627, 2002

      1 김영일, "하이브리드형 제약 외삽실험 계획법" 한국통계학회 19 (19): 65-75, 2012

      2 Limmun, W., "Using a Genetic Algorithm to Generate D-optimal Designs for Mixture Experiments" 29 : 1055-1068, 2013

      3 Dette, H., "Robust optimal extrapolation designs" 83 : 667-680, 1996

      4 Box, G. E. P., "Robust design" 62 : 347-352, 1975

      5 Kiefer, J., "Optimum extrapolation and interpolation designs" 16 : 79-108, 1964

      6 Hoel, P. G., "Optimal spacing and weighting in polynomial prediction" 35 : 1553-1560, 1964

      7 Stigler, S. M., "Optimal experimental design for polynomial regression" 66 : 311-318, 1971

      8 Studden, W. J., "Optimal designs for multivariate polynomial extrapolation" 42 : 828-832, 1971

      9 Cook, R. D., "On the equivalence between constrained and compound optimal designs" 89 : 687-692, 1994

      10 Myung-WookKahng, "Multiple Constrained Optimal Experimental Design" 한국통계학회 9 (9): 4-627, 2002

      11 Huang, M. L., "Model robust extrapolation designs" 18 : 1-24, 1988

      12 김영일, "Hybrid Approach When Multiple Objectives Exist" 한국통계학회 14 (14): 531-540, 2007

      13 Lauter, E., "Experimental planning in a class of models" 5 : 673-708, 1974

      14 Park, Y. J., "Cost- constrained G-efficient response surface designs for cuboidal regions" 22 : 121-139, 2005

      15 Imhof, L., "A graphical method for finding maximin designs" 56 : 113-117, 2000

      16 Wong, W. K., "A graphical approach for the construction of constrained D and L-optimal designs using efficiency plots" 53 : 143-152, 1995

      17 Jones, B., "A class of three-level designs for definitive screening in the presence of second-order Effects" 43 : 1-15, 2011

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2027 평가예정 재인증평가 신청대상 (재인증)
      2021-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2018-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2015-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2011-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2009-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2005-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2002-07-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2000-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.38 0.38 0.38
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.35 0.34 0.565 0.17
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