Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson

Autores:: Giraldo, Ramón
Zarruk, Armando
Riveros, Edwin

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	Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson
title	Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson
spellingShingle	Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson Distribución Burr XII datos censurados datos truncados máxima verosimilitud Burr XII distribution, censored and truncated data, maximum likelihood
title_short	Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson
title_full	Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson
title_fullStr	Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson
title_full_unstemmed	Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson
title_sort	Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson
dc.creator.fl_str_mv	Giraldo, Ramón Zarruk, Armando Riveros, Edwin
dc.contributor.author.spa.fl_str_mv	Giraldo, Ramón Zarruk, Armando Riveros, Edwin
dc.subject.none.fl_str_mv	Distribución Burr XII datos censurados datos truncados máxima verosimilitud Burr XII distribution, censored and truncated data, maximum likelihood
topic	Distribución Burr XII datos censurados datos truncados máxima verosimilitud Burr XII distribution, censored and truncated data, maximum likelihood
publishDate	2024
dc.date.accessioned.none.fl_str_mv	2024-12-11 00:00:00 2026-04-16T17:12:20Z
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.n2.2024.14858
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dc.relation.references.none.fl_str_mv	Burr I. Cumulative frequency functions. Annals of Mathematical Statistics. 1942; 2(13): 215-232. Hogg R, Klugman S. Loss Distributions. New York: John Wiley & Sons; 2009. Klugman S, Panjer H, Willmot G. Loss Models: From Data to Decisions. New York: John Wiley & Sons; 2012. Embrechts P, Klüppelberg C, Mikosch T. Modelling Extremal Events: for Insurance and Finance. New York: Springer Science & Business Media; 2013. Albrecher H, Beirlant J, Teugels J. Actuarial and Statistical Aspect. New York: John Wiley & Sons; 2017. Zimmer W, Keats J, Wang, F. The Burr XII distribution in reliability analysis. Journal of Quality Technology. 1998; 30(4):386-394. Rao G, Aslam M, Kundu D. Burr-XII distribution parametric estimation and estimation of reliability of multicomponent stress-strength. Communications in Statistics-Theory and Methods. 2015; 44(23):4953– 4961. Wingo D. Maximum likelihood methods for fitting the Burr type XII distribution to life test data. Biometrical Journal. 1983; 25(1):77-84. Shao Q, Zhou X. A new parametric model for survival data with long-term survivor. Statistics in Medicine. 2004; 23(22):3525-3543. Kleiber C, Kotz S. Statistical Size Distributions in Economics and Actuarial Sciences. New York: John Wiley & Sons; 2003. Beirlant J, Goegebeur Y, Verlaak R, Vynckier P. Burr regression and portfolio segmentation. Insurance: Mathematics and Economics. 1998; 23(3):231-250. Yourstone S, ZimmerW. Non-normality and the design of control charts for averages. Decision Sciences. 1992; 23(5):1099-1113. Chou C, Chen C, Liu H. Acceptance control charts for non-normal data. Journal of Applied Statistics. 2005; 32(1):25-36. Wingo D. Maximum likelihood methods for fitting the Burr type XII distribution to multiply (progressively) censored life test data. Metrika. 1993; 40(1):203-210. Wang F, Keats J, Zimmer W. Maximum likelihood estimation of the Burr XII parameters with censored and uncensored data. Microelectronics Reliability. 1996; 36(3):359-362. Ghitany M, Al-Awadhi S. Maximum likelihood estimation of Burr XII distribution parameters under random censoring. Journal of Applied Statistics. 2002; 29(7):955-965. A. Abuzaid. The estimation of the Burr-XII parameters with middle-censored data. SpringerPlus vol. 4, no. 1, pp 1-10, 2015. Aslam M, Mahmood Y, Lio Y, Tsai T, Khan M. Double acceptance sampling plans for Burr type XII distribution percentiles under the truncated life test. Journal of the Operational Research Society. 2012; 63(7):1010-1017. Tsai T, Lio Y, Jiang N, Lin Y, Fan Y. Economical sampling plans with warranty based on truncated data from Burr type XII distribution. Journal of the Operational Research Society. 2015; 66(9):1511-1518. Balakrishnan N, Mitra D. Left truncated and right censored Weibull data and likelihood inference with an illustration. Computational Statistics & Data Analysis. 2012; 56(12):4011-4025. Balakrishnan N, Mitra D. EM-based likelihood inference for some lifetime distributions based on left truncated and right censored data and associated model discrimination. South African Statistical Journal. 2014; 48(12):125-171. Kundu D, Mitra D. A. Analysis of left truncated and right censored competing risks data. Computational Statistics & Data Analysis. 2017; 108:12-26. Kundu D, Mitra D. Statistical inference based on left truncated and interval censored data from loglocation- scale family of distributions. Communications in Statistics Simulation and Computation. 2021; 50(4):1073-1093. Afify A, Cordeiro G, Ortega E, Yousof H, Butt N. The four-parameter Burr XII distribution: Properties, regression model, and applications. Communications in Statistics-Theory and Methods. 2018; 47(11):2605-2624. Paranaíba P, Ortega E, Cordeiro G, Pascoa M. The Kumaraswamy Burr XII distribution: theory and practice. Journal of Statistical Computation and Simulation. 2021; 83(11):2117-2143. Olapade A. On a six-parameter generalized Burr XII distribution. arXiv preprint 0806.1579:1–8. El-Bassiouny A, Abdo N. Reliability properties of seven parameters Burr XII distribution. Computational Methods in Science and Technology. 2010; 16:127-133. Adeyemi S, Adebanji A. Moments of order statistics from doubly truncated Burr XII distribution: A complementary note with applications. Journal of Statistical Research. 2015; 41(1):37-50. Gomes A, da-Silva C, Cordeiro, G. Two extended Burr models: Theory and practice. Journal of Applied Statistics. 2015; 44(8):1706-1734. Mead M. A new generalization of Burr XII distribution. Journal of Statistics: Advances in Theory and Applications. 2014; 12(2):53-73. Lanjoni B, Ortega E, Cordeiro G. Extended Burr XII regression models: theory and applications. Journal of Agricultural, Biological, and Environmental Statistics. 2016; 21(1):203-224. Shakhatreh M, Al-Masri A. On the weighted Burr XII distribution: theory and practice. Electronic Journal of Applied Statistical Analysis. 2015; 13(1):229-255. Süli E, Mayers, D. An Introduction to Numerical Analysis. 2003, Cambridge University Press. Efron B, Hinkley, D. Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information. Biometrika. 1978; 65(3): 457-483 Watkins, A. A note on expected fisher information for the Burr XII distribution. Microelectronics Reliability. 1997; 37(12), 1849-1852. Brazauskas, V. Information matrix for Pareto (IV), Burr, and related distributions. Communications in Statistics-Theory and Methods. 2003; 32(2), 315-325. Dutang C, Goulet V, Pigeon M. actuar: An R package for actuarial science, Journal of Statistical Software. 2008; 25(7):1-37. R Core Team. R. A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. 2018; https://www.R-project.org/. Okasha M, Matter M. On the three-parameter Burr type XII distribution and its application to heavy tailed lifetime data. Journal of Statistics: Advances in Theory and Applications. 2014; 12(2):53-73. Lee E, Wang, J. Statistical Methods for Survival Data Analysis. 2003, ohn Wiley & Sons. Al-Shomrani A, Shawky A, Arif O, Aslam, M. Log-logistic Distribution for Survival Data Analysis Using MCMC. SpringerPlus. 2016; 5:1-16.
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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	Giraldo, RamónZarruk, ArmandoRiveros, Edwin2024-12-11 00:00:002026-04-16T17:12:20Z2024-12-11 00:00:002024-12-110121-7488https://repositorio.uptc.edu.co/handle/001/1871810.19053/01217488.v15.n2.2024.148582462-7658https://doi.org/10.19053/01217488.v15.n2.2024.14858application/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/14858Distribución Burr XIIdatos censuradosdatos truncadosmáxima verosimilitudBurr XII distribution, censored and truncated data, maximum likelihoodDistribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-RaphsonArtículo 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_970fb48d4fbd8a85Burr I. Cumulative frequency functions. Annals of Mathematical Statistics. 1942; 2(13): 215-232.Hogg R, Klugman S. Loss Distributions. New York: John Wiley & Sons; 2009.Klugman S, Panjer H, Willmot G. Loss Models: From Data to Decisions. New York: John Wiley & Sons; 2012.Embrechts P, Klüppelberg C, Mikosch T. Modelling Extremal Events: for Insurance and Finance. New York: Springer Science & Business Media; 2013.Albrecher H, Beirlant J, Teugels J. Actuarial and Statistical Aspect. New York: John Wiley & Sons; 2017.Zimmer W, Keats J, Wang, F. The Burr XII distribution in reliability analysis. Journal of Quality Technology. 1998; 30(4):386-394.Rao G, Aslam M, Kundu D. Burr-XII distribution parametric estimation and estimation of reliability of multicomponent stress-strength. Communications in Statistics-Theory and Methods. 2015; 44(23):4953– 4961.Wingo D. Maximum likelihood methods for fitting the Burr type XII distribution to life test data. Biometrical Journal. 1983; 25(1):77-84.Shao Q, Zhou X. A new parametric model for survival data with long-term survivor. Statistics in Medicine. 2004; 23(22):3525-3543.Kleiber C, Kotz S. Statistical Size Distributions in Economics and Actuarial Sciences. New York: John Wiley & Sons; 2003.Beirlant J, Goegebeur Y, Verlaak R, Vynckier P. Burr regression and portfolio segmentation. Insurance: Mathematics and Economics. 1998; 23(3):231-250.Yourstone S, ZimmerW. Non-normality and the design of control charts for averages. Decision Sciences. 1992; 23(5):1099-1113.Chou C, Chen C, Liu H. Acceptance control charts for non-normal data. Journal of Applied Statistics. 2005; 32(1):25-36.Wingo D. Maximum likelihood methods for fitting the Burr type XII distribution to multiply (progressively) censored life test data. Metrika. 1993; 40(1):203-210.Wang F, Keats J, Zimmer W. Maximum likelihood estimation of the Burr XII parameters with censored and uncensored data. Microelectronics Reliability. 1996; 36(3):359-362.Ghitany M, Al-Awadhi S. Maximum likelihood estimation of Burr XII distribution parameters under random censoring. Journal of Applied Statistics. 2002; 29(7):955-965.A. Abuzaid. The estimation of the Burr-XII parameters with middle-censored data. SpringerPlus vol. 4, no. 1, pp 1-10, 2015.Aslam M, Mahmood Y, Lio Y, Tsai T, Khan M. Double acceptance sampling plans for Burr type XII distribution percentiles under the truncated life test. Journal of the Operational Research Society. 2012; 63(7):1010-1017.Tsai T, Lio Y, Jiang N, Lin Y, Fan Y. Economical sampling plans with warranty based on truncated data from Burr type XII distribution. Journal of the Operational Research Society. 2015; 66(9):1511-1518.Balakrishnan N, Mitra D. Left truncated and right censored Weibull data and likelihood inference with an illustration. Computational Statistics & Data Analysis. 2012; 56(12):4011-4025.Balakrishnan N, Mitra D. EM-based likelihood inference for some lifetime distributions based on left truncated and right censored data and associated model discrimination. South African Statistical Journal. 2014; 48(12):125-171.Kundu D, Mitra D. A. Analysis of left truncated and right censored competing risks data. Computational Statistics & Data Analysis. 2017; 108:12-26.Kundu D, Mitra D. Statistical inference based on left truncated and interval censored data from loglocation- scale family of distributions. Communications in Statistics Simulation and Computation. 2021; 50(4):1073-1093.Afify A, Cordeiro G, Ortega E, Yousof H, Butt N. The four-parameter Burr XII distribution: Properties, regression model, and applications. Communications in Statistics-Theory and Methods. 2018; 47(11):2605-2624.Paranaíba P, Ortega E, Cordeiro G, Pascoa M. The Kumaraswamy Burr XII distribution: theory and practice. Journal of Statistical Computation and Simulation. 2021; 83(11):2117-2143.Olapade A. On a six-parameter generalized Burr XII distribution. arXiv preprint 0806.1579:1–8.El-Bassiouny A, Abdo N. Reliability properties of seven parameters Burr XII distribution. Computational Methods in Science and Technology. 2010; 16:127-133.Adeyemi S, Adebanji A. Moments of order statistics from doubly truncated Burr XII distribution: A complementary note with applications. Journal of Statistical Research. 2015; 41(1):37-50.Gomes A, da-Silva C, Cordeiro, G. Two extended Burr models: Theory and practice. Journal of Applied Statistics. 2015; 44(8):1706-1734.Mead M. A new generalization of Burr XII distribution. Journal of Statistics: Advances in Theory and Applications. 2014; 12(2):53-73.Lanjoni B, Ortega E, Cordeiro G. Extended Burr XII regression models: theory and applications. Journal of Agricultural, Biological, and Environmental Statistics. 2016; 21(1):203-224.Shakhatreh M, Al-Masri A. On the weighted Burr XII distribution: theory and practice. Electronic Journal of Applied Statistical Analysis. 2015; 13(1):229-255.Süli E, Mayers, D. An Introduction to Numerical Analysis. 2003, Cambridge University Press.Efron B, Hinkley, D. Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information. Biometrika. 1978; 65(3): 457-483Watkins, A. A note on expected fisher information for the Burr XII distribution. Microelectronics Reliability. 1997; 37(12), 1849-1852.Brazauskas, V. Information matrix for Pareto (IV), Burr, and related distributions. Communications in Statistics-Theory and Methods. 2003; 32(2), 315-325.Dutang C, Goulet V, Pigeon M. actuar: An R package for actuarial science, Journal of Statistical Software. 2008; 25(7):1-37.R Core Team. R. A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. 2018; https://www.R-project.org/.Okasha M, Matter M. On the three-parameter Burr type XII distribution and its application to heavy tailed lifetime data. Journal of Statistics: Advances in Theory and Applications. 2014; 12(2):53-73.Lee E, Wang, J. Statistical Methods for Survival Data Analysis. 2003, ohn Wiley & Sons.Al-Shomrani A, Shawky A, Arif O, Aslam, M. Log-logistic Distribution for Survival Data Analysis Using MCMC. SpringerPlus. 2016; 5:1-16.134212515Ciencia en Desarrollohttps://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/download/14858/14867Núm. 2 , Año 2024 : Vol. 15 Núm. 2 (2024): Vol 15, Núm.2 (2024): Julio-DiciembrePublicationOREORE.xmltext/xml2778https://repositorio.uptc.edu.co/bitstreams/8485e91c-59a0-4e6f-8867-426ecb5e7127/downloadd8aaa8c0e084048f2a9abf010b209ee2MD51falseAnonymousREAD001/18718oai:repositorio.uptc.edu.co:001/187182026-10-30 07:02:33.612https://creativecommons.org/licenses/by-nc-nd/4.0/deed.esmetadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCbdigital@metabiblioteca.com

Distribución de Burr XII con datos truncados y censurados: Estimación de máxima verosimilitud basada en Método de Newton-Raphson

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