The effect of factor interactions in Plackett-Burman experimental designs: Comparison of Bayesian-Gibbs analysis and genetic algorithms

dc.creatorMagallanes, Jorge Federico
dc.creatorOlivieri, Alejandro Cesar
dc.date.accessioned2021-03-17T12:31:59Z
dc.date.accessioned2022-10-15T05:13:03Z
dc.date.available2021-03-17T12:31:59Z
dc.date.available2022-10-15T05:13:03Z
dc.date.created2021-03-17T12:31:59Z
dc.date.issued2010-05
dc.identifierMagallanes, Jorge Federico; Olivieri, Alejandro Cesar; The effect of factor interactions in Plackett-Burman experimental designs: Comparison of Bayesian-Gibbs analysis and genetic algorithms; Elsevier Science; Chemometrics and Intelligent Laboratory Systems; 102; 1; 5-2010; 8-14
dc.identifier0169-7439
dc.identifierhttp://hdl.handle.net/11336/128454
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4348466
dc.description.abstractA genetic algorithm has been developed in order to estimate not only the main effects but also the association of terms when analyzing the influence of experimental factors through a Plackett-Burman design of experiments. The results for a series of simulated systems as well as experimental examples show excellent agreement with a Bayesian-Gibbs approach. The Plackett-Burman design is usually employed for screening, but its performance depends on the assumption that the interaction effects are negligible. Simulations allow one to analyze the effect of increasing interactions on the significance of main factors when Plackett-Burman designs are processed by neglecting factor associations.
dc.languageeng
dc.publisherElsevier Science
dc.relationinfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0169743910000316
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.chemolab.2010.02.007
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectBAYESIAN-GIBBS ANALYSIS
dc.subjectEXPERIMENTAL DESIGN AND MODELING
dc.subjectFACTOR ASSOCIATIONS
dc.subjectGENETIC ALGORITHMS
dc.subjectPLACKETT-BURMAN DESIGNS
dc.titleThe effect of factor interactions in Plackett-Burman experimental designs: Comparison of Bayesian-Gibbs analysis and genetic algorithms
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/publishedVersion


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