Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response

Autores:: Rudnykh, Svetlana I.
López-Ríos, Victor Ignacio

Tipo de recurso:: Article of journal

Fecha de publicación:: 2024

Institución:: Universidad Pedagógica y Tecnológica de Colombia

Repositorio:: RiUPTC: Repositorio Institucional UPTC

Idioma:

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dc.title.es-ES.fl_str_mv	Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response
title	Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response
spellingShingle	Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response Diseños óptimos Bayesianos Funciones de Deseabilidad Modelo de Crecimiento Exponencial Diseños Penalizados Modelo de Regresión Cuadrática Bayesian Optimal Designs Desirability Functions Exponential Growth Model Penalized Designs Quadratic Regression Model
title_short	Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response
title_full	Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response
title_fullStr	Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response
title_full_unstemmed	Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response
title_sort	Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response
dc.creator.fl_str_mv	Rudnykh, Svetlana I. López-Ríos, Victor Ignacio
dc.contributor.author.spa.fl_str_mv	Rudnykh, Svetlana I. López-Ríos, Victor Ignacio
dc.subject.none.fl_str_mv	Diseños óptimos Bayesianos Funciones de Deseabilidad Modelo de Crecimiento Exponencial Diseños Penalizados Modelo de Regresión Cuadrática Bayesian Optimal Designs Desirability Functions Exponential Growth Model Penalized Designs Quadratic Regression Model
topic	Diseños óptimos Bayesianos Funciones de Deseabilidad Modelo de Crecimiento Exponencial Diseños Penalizados Modelo de Regresión Cuadrática Bayesian Optimal Designs Desirability Functions Exponential Growth Model Penalized Designs Quadratic Regression Model
publishDate	2024
dc.date.accessioned.none.fl_str_mv	2024-12-11 00:00:00 2026-04-16T17:12:21Z
dc.date.available.none.fl_str_mv	2024-12-11 00:00:00
dc.date.issued.none.fl_str_mv	2024-12-11
dc.type.spa.fl_str_mv	Artículo de revista
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dc.identifier.doi.none.fl_str_mv	10.19053/01217488.v15.n2.2024.15078
dc.identifier.eissn.none.fl_str_mv	2462-7658
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dc.relation.references.none.fl_str_mv	H. Chernoff, “Locally Optimal Designs for Estimating Parameters”, The Annals of Mathematical Statistics, vol. 24, no. 4, pp. 586-602, 1953. K. Chaloner and I. Verdinelli, “Bayesian experimental design: A review”, Statistical Science, vol. 10, no. 3, pp. 273-304, 1995. G. E. Box and N. R. Draper, “Robust designs”,Biometrika, vol. 62, no. 2, pp. 347-352, 1975. V. Dragalin and V. Fedorov, “Adaptive designs for dose-finding based on efficacy-toxicity response”, Journal of Statistical Planning and Inference, vol. 136, no. 6, pp. 1800-1823, 2006. V. Dragalin, V. Fedorov and Y. Wu, “Adaptive designs for selecting drug combinations based on efficacy-toxicity response”, Journal of Statistical Planning and Inference, vol. 138, no. 2, pp. 352-373, 2008. L. Pronzato, “Penalized optimal designs for dose-finding”, Journal of Statistical Planning and Inference, vol. 140, no. 1, pp. 283-296, 2010. S. M. Parker and C. Gennings, “Penalized locally optimal experimental designs for nonlinear models”, Journal of agricultural, biological, and environmental statistics, vol. 13, no. 3, pp. 334-354, 2008. F.-C. Wu, “Optimization of correlated multiple quality characteristics using desirability function”, Quality Engineering, vol. 17, no. 1, pp. 119-126, 2004. E. C. Harrington, “The desirability function”, Industrial quality control, vol. 21, no. 10, pp. 494-498, 1965. S. I. Rudnykh y V. I. López Ríos, “Elección de la función de deseabilidad para diseños óptimos bajo restricciones”, Revista EIA, vol. 15, no. 30, pp. 13-24, 2018. M. Shih, C. Gennings, V.M. Chinchilli and W.H Carter Jr, “Titrating and evaluating multidrug regimens within subjects”, Statistics in medicine, vol. 22, no. 14, pp. 2257-2279, 2003. A. DasGupta and W. Studden, “Robust bayesian experimental designs in normal linear models”, The Annals of Statistics, vol. 19, no. 3, pp. 1244-1256, 1991. J. A. Nelder and R. Mead, “A simplex method for function minimization”, The computer journal, vol. 7, no. 4, pp. 308-313, 1965. J. Pilz, “Bayesian estimation and experimental design in linear regression models”. JohnWiley & Sons Inc, NY, 1991. R. D. Gibb, “Optimal treatment combination estimation for univariate and multivariate response surface applications”. Ph.D. thesis Virginia Commonwealth University, Richmond, Virginia, USA, 1998. R Core Team “R: A language and environment for statistical computing”. R foundation for statistical computing, Vienna, Austria, 2021, https://www.r-project.org/ S. M. Ermakov and A. A. Zhiglijavsky, “Matematitscheskaja teorija optimalnich experimentov”. Nauka, Moskva, 1987. V. V. Fedorov and S. L. Leonov, “Optimal design for nonlinear response models”. CRC Press, 2013. H. Dette and S. Sperlich, “A Note on Bayesian D-optimal Designs for a Generalization of the Exponential Growth Model”, South African Statistical Journal, vol. 28, pp. 103-117, 1994. D. Firth and J. Hinde, “On Bayesian Doptimum Design Criteria and the Equivalence Theorem in Non-linear Models.”, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 59, no. 4, pp. 793-797, 1997. B. P. Duarte and W. K. Wong, “Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming-Based Approach”, International Statistical Review, vol. 83, no. 2, pp. 239-262, 2015. S. Mukhopadhyay and L. M. Haines, “Bayesian D-optimal Designs for the Exponential Growth Model.”, Journal of Statistical Planning and Inference, vol. 44, no. 3, pp. 385-397, 1995. S. I. Rudnykh, “Penalized bayesian optimal designs for nonlinear models of Continuous Response”. Ph.D. thesis Universidad Nacional de Colombia, Medellín, Colombia, 2020.
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dc.relation.ispartofjournal.spa.fl_str_mv	Ciencia en Desarrollo
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dc.relation.citationedition.spa.fl_str_mv	Núm. 2 , Año 2024 : Vol. 15 Núm. 2 (2024): Vol 15, Núm.2 (2024): Julio-Diciembre
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spelling	Rudnykh, Svetlana I.López-Ríos, Victor Ignacio2024-12-11 00:00:002026-04-16T17:12:21Z2024-12-11 00:00:002024-12-110121-7488https://repositorio.uptc.edu.co/handle/001/1871910.19053/01217488.v15.n2.2024.150782462-7658https://doi.org/10.19053/01217488.v15.n2.2024.15078application/pdfUniversidad Pedagógica y Tecnológica de Colombiahttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.esinfo:eu-repo/semantics/openAccessEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.http://purl.org/coar/access_right/c_abf2https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/view/15078Diseños óptimos BayesianosFunciones de DeseabilidadModelo de Crecimiento ExponencialDiseños PenalizadosModelo de Regresión CuadráticaBayesian Optimal DesignsDesirability FunctionsExponential Growth ModelPenalized DesignsQuadratic Regression ModelPenalized Bayesian D-Optimal Designs for Regression Models of Continuous ResponseArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/coar/version/c_970fb48d4fbd8a85H. Chernoff, “Locally Optimal Designs for Estimating Parameters”, The Annals of Mathematical Statistics, vol. 24, no. 4, pp. 586-602, 1953.K. Chaloner and I. Verdinelli, “Bayesian experimental design: A review”, Statistical Science, vol. 10, no. 3, pp. 273-304, 1995.G. E. Box and N. R. Draper, “Robust designs”,Biometrika, vol. 62, no. 2, pp. 347-352, 1975.V. Dragalin and V. Fedorov, “Adaptive designs for dose-finding based on efficacy-toxicity response”, Journal of Statistical Planning and Inference, vol. 136, no. 6, pp. 1800-1823, 2006.V. Dragalin, V. Fedorov and Y. Wu, “Adaptive designs for selecting drug combinations based on efficacy-toxicity response”, Journal of Statistical Planning and Inference, vol. 138, no. 2, pp. 352-373, 2008.L. Pronzato, “Penalized optimal designs for dose-finding”, Journal of Statistical Planning and Inference, vol. 140, no. 1, pp. 283-296, 2010.S. M. Parker and C. Gennings, “Penalized locally optimal experimental designs for nonlinear models”, Journal of agricultural, biological, and environmental statistics, vol. 13, no. 3, pp. 334-354, 2008.F.-C. Wu, “Optimization of correlated multiple quality characteristics using desirability function”, Quality Engineering, vol. 17, no. 1, pp. 119-126, 2004.E. C. Harrington, “The desirability function”, Industrial quality control, vol. 21, no. 10, pp. 494-498, 1965.S. I. Rudnykh y V. I. López Ríos, “Elección de la función de deseabilidad para diseños óptimos bajo restricciones”, Revista EIA, vol. 15, no. 30, pp. 13-24, 2018.M. Shih, C. Gennings, V.M. Chinchilli and W.H Carter Jr, “Titrating and evaluating multidrug regimens within subjects”, Statistics in medicine, vol. 22, no. 14, pp. 2257-2279, 2003.A. DasGupta and W. Studden, “Robust bayesian experimental designs in normal linear models”, The Annals of Statistics, vol. 19, no. 3, pp. 1244-1256, 1991.J. A. Nelder and R. Mead, “A simplex method for function minimization”, The computer journal, vol. 7, no. 4, pp. 308-313, 1965.J. Pilz, “Bayesian estimation and experimental design in linear regression models”. JohnWiley & Sons Inc, NY, 1991.R. D. Gibb, “Optimal treatment combination estimation for univariate and multivariate response surface applications”. Ph.D. thesis Virginia Commonwealth University, Richmond, Virginia, USA, 1998.R Core Team “R: A language and environment for statistical computing”. R foundation for statistical computing, Vienna, Austria, 2021, https://www.r-project.org/S. M. Ermakov and A. A. Zhiglijavsky, “Matematitscheskaja teorija optimalnich experimentov”. Nauka, Moskva, 1987.V. V. Fedorov and S. L. Leonov, “Optimal design for nonlinear response models”. CRC Press, 2013.H. Dette and S. Sperlich, “A Note on Bayesian D-optimal Designs for a Generalization of the Exponential Growth Model”, South African Statistical Journal, vol. 28, pp. 103-117, 1994.D. Firth and J. Hinde, “On Bayesian Doptimum Design Criteria and the Equivalence Theorem in Non-linear Models.”, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 59, no. 4, pp. 793-797, 1997.B. P. Duarte and W. K. Wong, “Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming-Based Approach”, International Statistical Review, vol. 83, no. 2, pp. 239-262, 2015.S. Mukhopadhyay and L. M. Haines, “Bayesian D-optimal Designs for the Exponential Growth Model.”, Journal of Statistical Planning and Inference, vol. 44, no. 3, pp. 385-397, 1995.S. I. Rudnykh, “Penalized bayesian optimal designs for nonlinear models of Continuous Response”. Ph.D. thesis Universidad Nacional de Colombia, Medellín, Colombia, 2020.1692162215Ciencia en Desarrollohttps://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/download/15078/14904Núm. 2 , Año 2024 : Vol. 15 Núm. 2 (2024): Vol 15, Núm.2 (2024): Julio-DiciembrePublicationOREORE.xmltext/xml2669https://repositorio.uptc.edu.co/bitstreams/f130d393-7dfe-488f-9464-fdd478357488/download54cc3dc1ec6bdddbfada64c94fe2c6ebMD51falseAnonymousREAD001/18719oai:repositorio.uptc.edu.co:001/187192026-10-30 07:02:03.056https://creativecommons.org/licenses/by-nc-nd/4.0/deed.esmetadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCbdigital@metabiblioteca.com

Penalized Bayesian D-Optimal Designs for Regression Models of Continuous Response

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