The effect of factor interactions in Plackett-Burman experimental designs: Comparison of Bayesian-Gibbs analysis and genetic algorithms | ||
| dc.conicet.fuente | individual | |
| dc.conicet.organizacion | Comisión Nacional de Energía Atómica | |
| dc.conicet.organizacion | Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario | |
| dc.conicet.organizacion | Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica | |
| dc.conicet.paisOrganizacion | Argentina | |
| dc.conicet.paisOrganizacion | Argentina | |
| dc.conicet.paisOrganizacion | Argentina | |
| dc.conicet.produccionid | 4890926 | |
| dc.contributor.author | Magallanes, Jorge Federico | |
| dc.contributor.author | Olivieri, Alejandro Cesar | |
| dc.date.accessioned | 2021-03-17T12:31:59Z | |
| dc.date.available | 2021-03-17T12:31:59Z | |
| dc.date.issued | 2010-05 | |
| dc.date.updated | 2021-02-18T15:22:37Z | |
| dc.description.abstract | A 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. | es |
| dc.description.fil | Fil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; Argentina | |
| dc.description.fil | Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Química Analítica; Argentina | |
| dc.format | application/pdf | es |
| dc.identifier.citation | Magallanes, 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 | es |
| dc.identifier.institucional | CONICET | |
| dc.identifier.issn | 0169-7439 | es |
| dc.identifier.repo | CONICET Digital | |
| dc.identifier.uri | http://hdl.handle.net/11336/128454 | |
| dc.journal.ciudad | Amsterdam | es |
| dc.journal.number | 1 | es |
| dc.journal.pagination | 8-14 | es |
| dc.journal.pais | Países Bajos | es |
| dc.journal.title | Chemometrics and Intelligent Laboratory Systems | es |
| dc.journal.volume | 102 | es |
| dc.language.iso | eng | es |
| dc.publisher | Elsevier Science | es |
| dc.relation.alternativeid | info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0169743910000316 | |
| dc.relation.alternativeid | info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.chemolab.2010.02.007 | |
| dc.rights | info:eu-repo/semantics/openAccess | * |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | * |
| dc.subject | BAYESIAN-GIBBS ANALYSIS | es |
| dc.subject | EXPERIMENTAL DESIGN AND MODELING | es |
| dc.subject | FACTOR ASSOCIATIONS | es |
| dc.subject | GENETIC ALGORITHMS | es |
| dc.subject | PLACKETT-BURMAN DESIGNS | es |
| dc.subject.classification | Química Analítica | es |
| dc.subject.classification | Ciencias Químicas | es |
| dc.subject.classification | CIENCIAS NATURALES Y EXACTAS | es |
| dc.title | The effect of factor interactions in Plackett-Burman experimental designs: Comparison of Bayesian-Gibbs analysis and genetic algorithms | es |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:ar-repo/semantics/artículo | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
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