One-Step Screening and Process Optimization Experiments.
The writer examines certain orthogonal array experiments and provides examples of one-step screening and optimization. He contends that one-step screening and optimization experiments are a feasible alternative to sequential experimentation limited by time or budget. He also suggests that some des...
| Publicado en: | American Statistician Vol. 57; no. 1; pp. 15 - 21 |
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| Formato: | Artículo |
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American Statistical Association
February 2003
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=507809095&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 507809095 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: N pubinfo: dt: February 2003 vid: 57 iid: 1 pid: 543 pub: American Statistical Association artinfo: ui: 507809095 10.1198/0003130031045 ppf: 15 ppct: 6 formats: tig: atl: One-Step Screening and Process Optimization Experiments. aug: au: Lawson, John su: Experimental design Mathematical optimization Statistics sug: subj: Experimental design Mathematical optimization Statistics ab: The writer examines certain orthogonal array experiments and provides examples of one-step screening and optimization. He contends that one-step screening and optimization experiments are a feasible alternative to sequential experimentation limited by time or budget. He also suggests that some designs thought to be useful for only screening experiments can also be useful for detecting interactions, fitting quadratic models to a subset of the factors, and identifying optimal operating conditions within the ranges studied when they are combined with suitable methods of data analysis. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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