dc.contributor.author | Tyssedal, John Sølve | |
dc.contributor.author | Kulahci, Murat | |
dc.date.accessioned | 2018-04-24T11:15:50Z | |
dc.date.available | 2018-04-24T11:15:50Z | |
dc.date.created | 2018-01-02T13:55:25Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Journal of Applied Statistics. 2017, 44 (3), 493-510. | nb_NO |
dc.identifier.issn | 0266-4763 | |
dc.identifier.uri | http://hdl.handle.net/11250/2495668 | |
dc.description.abstract | Most of today’s complex systems and processes involve several stages through which input or the raw material has to go before the final product is obtained. Also in many cases factors at different stages interact. Therefore, a holistic approach for experimentation that considers all stages at the same time will be more efficient. However, there have been only a few attempts in the literature to provide an adequate and easy-to-use approach for this problem. In this paper, we present a novel methodology for constructing two-level split-plot and multistage experiments. The methodology is based on the Kronecker product representation of orthogonal designs and can be used for any number of stages, for various numbers of subplots and for different number of subplots for each stage. The procedure is demonstrated on both regular and nonregular designs and provides the maximum number of factors that can be accommodated in each stage. Furthermore, split-plot designs for multistage experiments with good projective properties are also provided. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Taylor & Francis | nb_NO |
dc.title | Split-plot designs for multistage Experimentation | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.pagenumber | 493-510 | nb_NO |
dc.source.volume | 44 | nb_NO |
dc.source.journal | Journal of Applied Statistics | nb_NO |
dc.source.issue | 3 | nb_NO |
dc.identifier.doi | 10.1080/02664763.2016.1177497 | |
dc.identifier.cristin | 1533822 | |
dc.description.localcode | This is an [Accepted Manuscript] of an article published by Taylor & Francis in [Journal of Applied Statistics] on [04 May 2016], available at https://www.tandfonline.com/doi/full/10.1080/02664763.2016.1177497 | nb_NO |
cristin.unitcode | 194,63,15,0 | |
cristin.unitname | Institutt for matematiske fag | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |