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A generalization of the alias matrix
Department of Industrial Engineering, Arizona State University, Tempe.
Isenberg School of Management, University of Massachusetts Amherst, Eugene M. Isenberg School of Management, University of Massachusetts Amherst.
2006 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 33, no 4, p. 387-395Article in journal (Refereed) Published
Abstract [en]

The investigation of aliases or biases is important for the interpretation of the results from factorial experiments. For two-level fractional factorials this can be facilitated through their group structure. For more general arrays the alias matrix can be used. This tool is traditionally based on the assumption that the error structure is that associated with ordinary least squares. For situations where that is not the case, we provide in this article a generalization of the alias matrix applicable under the generalized least squares assumptions. We also show that for the special case of split plot error structure, the generalized alias matrix simplifies to the ordinary alias matrix

Place, publisher, year, edition, pages
2006. Vol. 33, no 4, p. 387-395
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
URN: urn:nbn:se:ltu:diva-3760DOI: 10.1080/02664760500449014Local ID: 19700332-4c46-4bc5-a33c-06178284ef4bOAI: oai:DiVA.org:ltu-3760DiVA: diva2:976621
Note
Upprättat; 2006; 20150604 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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Kulahci, Murat
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