Distribución Bivariada Birnbaum-Saunders Unitaria

ilustraciones

Autores:: Rodríguez Quevedo, Luisa Paulina

Tipo de recurso:

Fecha de publicación:: 2023

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

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dc.title.spa.fl_str_mv	Distribución Bivariada Birnbaum-Saunders Unitaria
dc.title.translated.eng.fl_str_mv	Bivariate unit-Birnbaum-Saunders distribution
title	Distribución Bivariada Birnbaum-Saunders Unitaria
spellingShingle	Distribución Bivariada Birnbaum-Saunders Unitaria 510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas Statistical hypothesis testing Mathematical statistics Prueba de hipótesis estadística Estadística matemática Distribución Bivariada Birnbaum Saunders unitaria condicionalmente especificada Modelo de regresión multivariado Distibución Sinh-Normal Unitaria Datos acotados Distribución log-Birbaum Saunders multivariada Bivariate unit-Birnbaum-Saunders distribution Conditionally specified Multivariate regression model Unit-Sinh-Normal distribution Multivariate log-Birnbaum Saunders distribution Bounded data
title_short	Distribución Bivariada Birnbaum-Saunders Unitaria
title_full	Distribución Bivariada Birnbaum-Saunders Unitaria
title_fullStr	Distribución Bivariada Birnbaum-Saunders Unitaria
title_full_unstemmed	Distribución Bivariada Birnbaum-Saunders Unitaria
title_sort	Distribución Bivariada Birnbaum-Saunders Unitaria
dc.creator.fl_str_mv	Rodríguez Quevedo, Luisa Paulina
dc.contributor.advisor.none.fl_str_mv	Vergara Cardozo, Sandra Martínez Flórez, Guillermo
dc.contributor.author.none.fl_str_mv	Rodríguez Quevedo, Luisa Paulina
dc.subject.ddc.spa.fl_str_mv	510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas
topic	510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas Statistical hypothesis testing Mathematical statistics Prueba de hipótesis estadística Estadística matemática Distribución Bivariada Birnbaum Saunders unitaria condicionalmente especificada Modelo de regresión multivariado Distibución Sinh-Normal Unitaria Datos acotados Distribución log-Birbaum Saunders multivariada Bivariate unit-Birnbaum-Saunders distribution Conditionally specified Multivariate regression model Unit-Sinh-Normal distribution Multivariate log-Birnbaum Saunders distribution Bounded data
dc.subject.lemb.eng.fl_str_mv	Statistical hypothesis testing Mathematical statistics
dc.subject.lemb.spa.fl_str_mv	Prueba de hipótesis estadística
dc.subject.lemb.eps.fl_str_mv	Estadística matemática
dc.subject.proposal.spa.fl_str_mv	Distribución Bivariada Birnbaum Saunders unitaria condicionalmente especificada Modelo de regresión multivariado Distibución Sinh-Normal Unitaria Datos acotados Distribución log-Birbaum Saunders multivariada
dc.subject.proposal.eng.fl_str_mv	Bivariate unit-Birnbaum-Saunders distribution Conditionally specified Multivariate regression model Unit-Sinh-Normal distribution Multivariate log-Birnbaum Saunders distribution Bounded data
description	ilustraciones
publishDate	2023
dc.date.accessioned.none.fl_str_mv	2023-04-24T21:37:03Z
dc.date.available.none.fl_str_mv	2023-04-24T21:37:03Z
dc.date.issued.none.fl_str_mv	2023
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv	Text
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status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/83771
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/83771 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.relation.references.spa.fl_str_mv	Ahmed, S., Castro-Kuriss, C., Leiva, V., Flores, E., and Sanhueza, A. (2010). Truncated version of the birnbaum–saunders distribution with an application in financial risk. Pakistan Journal of Statistics, 26:293–311 Arnold, B., Castillo, E., and Sarabia, J. (2002). Conditionally specified multivariate skewed distributions. The Indian Journal of Statistics, 64(2):206–226. http: //www.jstor.org/stable/25051391 Athayde, E. (2017). A characterization of the birnbaum–saunders distribution. REVSTAT Statistical Journal, 15:333–354 Azzalini, A. (1985). A class of distributions which includes the normal ones. Scandinavian Journal of Statistics, 12(2):171–178. http://www.jstor.org/stable/ 4615982 Barlow, R. and Proschan, F. (1965). Mathematical theory of reliability. Wiley, 1 Barros, M., Galea, M., Gonzalez, M., and Leiva, V. (2010). Infuence diagnostics in the tobit censored response model. Stat. Methods Appl., 19:379–397. https: //doi.org/10.1007/s10260-010-0135-y Bartlett, M. and Kendall, D. (1946). The statistical analysis of variance-heterogeneity and the logarithmic transformation. Journal of the Royal Statistical Society: Series B, 8(1):128–138. https://doi.org/10.2307/2983618 Bebbington, M., Lai, C., and Zitikis, R. (2008). A proof of the shape of the birnbaum–saunders hazard rate function. Mathematical Scientist, 33:49–56 Birnbaum, Z., Esary, J., and Marshall, A. (1966). Stochastic characterization of wear-out for components and systems. Annals of Mathematical Statistics, 37:816–825. https://www.jstor.org/stable/2238571 Birnbaum, Z. W. and Saunders, S. (1969). A new family of life distributions. Journal of Applied Probability, 6(2):319–327. https://doi.org/10. 2307/3212003 Cepeda Cuervo, E., Achcar, J., and Garrido Lopera, B. (2014). Bivariate beta regression models: Joint modeling of the mean, dispersion and association parameters. Journal of Applied Statistics, 41. https://doi.org/10.1080/02664763. 2013.847071 Chhikara, R. and Folks, J. (1977). The inverse gaussian distribution as a lifetime model. Technometrics, 19(4):461–468. https://doi.org/10.2307/ 1267886 Cook, D., Kieschnick, R., and McCullough, B. (2008). Regression analysis of proportions in finance with self selection. Journal of Empirical Finance, 15:860–867. https://doi.org/10.1016/j.jempfin.2008.02.001 Desmond, A. (1985). Stochastic models of failure in random environments. Statistical Society of Canada, 13(3):171–183. https://doi.org/10.2307/3315148 Davis, J. (1952). An analysis of some failure data. Journal of the American Statistical Association, 47:113–150. https://doi.org/10.2307/2280740 Dupuis, D. and Mills, J. (1998). Robust estimation of the birnbaum-saunders distribution. IEEE Transactions on Reliability, 47:88–95 Esary, J. and Marshall, A. (1973). Shock models and wear processes. The Annals of Probability, 1:627–649. https://www.jstor.org/stable/2959434 Farias, R. and Lemonte, A. (2011). Bayesian inference for the birnbaum–saunders nonlinear regression model. Statistical Methods and Applications, 20:423–438. https://doi.org/10.1007/s10260-011-0165-0 Díaz, J. and Leiva, V. (2005). A new family of life distributions based on the elliptically contoured distributions. Journal of Statistical Planning and Inference, 128:445–457. https://www.sciencedirect.com/science/article/pii/ S0378375804000072 Díaz-García, J. and Domínguez-Molina, J. (2006). Some generalisations of birnbaum–saunders and sinh-normal distributions. International Mathematical Forum, 1:1709–1727. http://dx.doi.org/10.12988/imf.2006. 06146 Freeman, D. (2007). Drunk driving legislation and traffic fatalities: New evidence on bac 08 laws. Contemporary Economic Policy 25, 293–308 Freudenthal, A. and Shinozuka, M. (1961). Structural Safety Under Conditions of Ultimate Load Failure and Fatigue. Wright Air Development Division Galea, M., Leiva, V., and Paula, G. (2004). Influence diagnostics in log-birnbaum–saunders regression models. Journal of Applied Statistics, 31:1049–1064. https://doi.org/10.1080/0266476042000280409 Garcia, F., Uribe, M., Leiva, V., and Aykroyd, G. (2017). Birnbaumsaunders spatial modelling and diagnostics applied to agricultural engineering data. Stochastic Environmental Research and Risk Assessment, 31:105–124. https://doi.org/ 10.1007/s00477-015-1204-4 Guiraud, P., Leiva, V., and Fierro, R. (2009). A non-central version of the birnbaum–saunders distribution for reliability analysis. IEEE Transactions on Reliability., 58:152–160. https://ieeexplore.ieee.org/document/4781589 Gupta, A. and Nadarajah, S. (2004). Handbook of Beta Distribution and Applications. CRC Press Kumaraswamy, P. (1980). A generalized probability density function for double-bounded random processes. Journal of Hydrology, 46:79–88. https://doi. org/10.1016/0022-1694(80)90036-0 Kundu, D. (2015). Bivariate log-birnbaum-saunders distribution. Statistics, 49:900–917. https://doi.org/10.1080/02331888.2014.915840 Kundu, D., N. Balakrishnan, B., and Jamalizadeh, A. (2010). Bivariate birnbaum–saunders distribution and associated inference. Journal of Multivariate Analysis, 101:113–125. https://doi.org/10.1016/j.jmva.2009.05.005 Kundu, D., Narayanaswamy, B., and Jamalizadeh, A. (2013). Generalized multivariate birnbaum–saunders distributions and related inferential issues. Journal of Multivariate Analysis, 40:230–244. https://doi.org/10.1016/j.jmva.2012.10.017 Leiva, V. (2016). The Birnbaum Saunders distribution, volume 1. Elsevier Leiva, V., Riquelme, M., Balakrishnan, N., and Sanhueza, A. (2006). A new fatigue life model based on the family of skew-elliptical distributions. Stat. Theory Methods, 35:229–244 Leiva, V., Riquelme, M., Balakrishnan, N., and Sanhueza, A. (2008). Lifetime analysis based on the generalized birnbaum–saunders distribution. Computational Statistics Data Analysis, 52:2079–2097. https://doi.org/10.1016/j.csda.2007.07. 003 Leiva, V., Soto, G., Cabrera, E., and Cabrera, G. (2011). Nuevas cartas de control basadas en la distribución Birnbaum-Saunders y su implementación. Revista Colombiana de Estadística, 34:147–176 Leiva, V., Vilca-Labra, F., Balakrishnan, N., and Sanhueza, A. (2010). A skewed sinh-normal distribution and its properties and application to air pollution. Communications in Statistics - Theory and Methods, 39:426–443. https://doi.org/10. 1080/03610920903140171 Lemonte, A. (2013). Multivariate birnbaum–saunders regression model. Journal of Statistical Computation and Simulation, 83(12):2244–2257. https://doi.org/ 10.1080/00949655.2012.688054 Lemonte, A. (2016). A note on the fisher information matrix of the birnbaum– saunders distribution. Journal of Statistical Theory and Applications, 15:196–205. https://doi.org/10.2991/jsta.2016.15.2.9 Lemonte, A. and Moreno-Arenas, G. (2019). On a multivariate regression model for rates and proportions. Journal of Applied Statistics, 46:1084–1106. https://doi.org/10.1080/02664763.2018.1534945 Lemonte, A. J. (2012). A log- birnbaum saunders regression model with asymmetric errors. Journal of Statistical Computation and Simulation, 82:1775–1787. https://doi.org/10.1080/00949655.2011.595715 Lieblein, J. (1956). Statistical investigation of the fatigue life of deep ball bearing. Journal of National Bureau of Standards, 57:273–316 Martínez-Flórez, G. and Tovar-Falón, R. (2021). New regression models based on the unit-sinh-normal distributions: Properties, inference, and applications. Mathematics, 9(11), 1231. https://doi.org/10.3390/math9111231 Martínez-Flórez, G., Azevedo, R., and Moreno-Arenas, G. (2017). Multivariate log-birnbaum–saunders regression models. Communications in Statistics - Theory and Methods, 46:10166–10178. https://doi.org/10.1080/03610926. 2016.1231818 Mazucheli, J., Leiva, V., Alves, B., and Menezes, A. (2021). A new quantile regression for modeling bounded data under a unit birnbaum- saunders distribution with aplplications in medicine and politics. Symmetry, 13(4):682. https: //doi.org/10.3390/sym13040682 Martínez-Flórez, G., Vergara-Cardozo, S., Tovar-Falón, R., and Rodriguez-Quevedo, L. (2023). The multivariate skewed log-birnbaum saunders distribution and its associated regression model. Mathematics, 11(5), 1095. http: //dx.doi.org/10.3390/math11051095 Mazucheli, J., Menezes, A., and Dey, S. (2018a). The unit birnbaum- saunders distribution with applications. Chilean Journal of Statistics, 9:47– 57 Mazucheli, J., Menezes, F., and Ghitany, M. (2018b). The unit weibull distribution and associated inference. Journal of Applied Probability and Statistics, 13:1–22 Miner, M. (1945). Cumulative damage in fatigue. Journal of Applied Mechanics, 12(3):A159–A164. https://doi.org/10.1115/1.4009458 Nelson, W. and Hahn, G. (1972). Linear estimation of a regression relationships from censored data, part i-simple methods and their applications. Technometrics, 14:247–269. https://doi.org/10.1080/00401706.1972.10488912 Ortega, E., Bolfarine, H., and Paula, G. (2003). Infuence diagnostics in generalized log-gamma regression models. Computational Statistics Data Analysis, 42:165–186. https://doi.org/10.1016/S0167-9473(02)00104-4 Owen, W. and Padgett, W. (1999). Accelerated test models for system strength based on birnbaum–saunders distribution. Lifetime Data Analysis, 5(2):133–147. https://doi.org/10.1023/A:1009649428243 R Core Team (2022). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www. R-project.org/ Rieck, J. and Nedelman, J. (1991). A log-linear model for the birnbaum–saunders distribution. Technometrics, 33(1):51–60. https://doi.org/ 10.2307/1269007 Shea, J. and Brown, K. (2022). Wooldridge: 115 data sets. In Introductory Econometrics: A Modern Approach, 7e, R package version 1.4-2 Vilca, F., Narayanaswamy, B., and C., B. (2014). A robust extension of the bivariate birnbaum–saunders distribution and associated inference. Journal of Multivariate Analysis, 35:418–435. https://doi.org/10.1016/j.jmva.2013.11.005 Volodin, I. and Dzhungurova, O. (2000). On limit distribution emerging in the generalized birnbaum–saunders model. Journal of Mathematical Science, 99:1348–66. https://doi.org/10.1007/BF02674095 Xie, F. and Wei, B. (2007). Diagnostics analysis for logbirnbaum– saunders regression models. Computational Statistics y Data Analysis, 51:4692– 4706. https://doi.org/10.1016/j.csda.2006.08.030 Zelen, M. and Dannemiller, M. (1961). The robustness of life testing procedures derived from the exponential distribution. Technometrics, 3(1):29–49. https://doi.org/10.2307/1266475 Lemonte, A., Martínez-Florez, G., and Moreno-Arenas, G. (2015b). Multivariate birnbaum–saunders distribution: Properties and associated inference. Journal of Statistical Computation and Simulation, 85:374–392. https://doi.org/10.1080/ 00949655.2013.823964 Lemonte, A., Martínez, G., and Moreno-Arenas, G. (2015a). Multivariate birnbaum–saunders distribution: properties and associated inference. Journal of Statistical Computation and Simulation, 1:374–392. https://doi.org/10.1080/ 00949655.2013.823964 Martínez-Flórez, G., Bolfarine, H., and Gómez, H. (2015). Doubly censored power-normal regression models with inflation. Journal of Theoretical and Applied Statistics, 24:265–286. https://doi.org/10.1007/s11749-014-0406-2 Kao, J. (1959). A graphical estimation of mixed weibull parameters in life-testing of electron tubes. Technometrics, 1:389–407. https://doi.org/10.2307/1266719
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dc.rights.license.spa.fl_str_mv	Atribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rights.uri.spa.fl_str_mv	http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.format.extent.spa.fl_str_mv	xii, 68 páginas
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Bogotá - Ciencias - Maestría en Ciencias - Estadística
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ciencias
dc.publisher.place.spa.fl_str_mv	Bogotá,Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Bogotá
institution	Universidad Nacional de Colombia
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spelling	Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Vergara Cardozo, Sandra01b852ce6a19d141eb1a301b12184a43Martínez Flórez, Guillermo5a3b256c373c5ef4f3fefde740a23496Rodríguez Quevedo, Luisa Paulina8f0823221596ef2b5a23957fb9c31e372023-04-24T21:37:03Z2023-04-24T21:37:03Z2023https://repositorio.unal.edu.co/handle/unal/83771Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustracionesLa distribución Unitaria Birnbaum Saunders (UBS), [Mazucheli et al., 2018a], tiene soporte en el intervalo (0,1), motivo por el cual se emplea con éxito en el modelamiento de tasas e indicadores. Se presentan dos nuevas distribuciones bivariadas, la distribución Bivariada Birnbaum Saunders Unitaria (BVUBS) y la distribución Bivariada Sinh-Normal Birnbaum Saunders Unitaria (BVUSHN), además como efecto natural el modelo de regresión para el caso de covariables en el modelo, empleando para ello el concepto de distribuciones condicionalmente especificadas, dichas distribuciones son capaces de modelar tasas y proporciones en el plano unidad, y presentan un mejor ajuste a datos comparadas con otras distribuciones. Igualmente, se presentan algunas propiedades generales de los modelos, valores esperados e inferencia por máxima verosimilitud y aplicación a datos reales. Conjuntamente al presente trabajo de maestría se publica el artículo The Multivariate Skewed Log-Birnbaum–Saunders Distribution and Its Associated Regression Model, [Martínez-Flórez et al., 2023], el cual se enfocó en la extensión multivariada de la distribución Sinh-Normal Unitaria, estudiando en detalle las propiedades de la distribución e inferencia estadística, se incluye un estudio de simulación asociado al modelo de regresión y dos aplicaciones con datos reales, logrando concluir que son potencialmente útiles para modelar datos de proporciones, tasas o índices. (Texto tomado de la fuente)The unit-Birnbaum-Saunders distribution (UBS), [Mazucheli et al., 2018a], has support in the interval (0,1), which is why it is used successfully in the modeling of rates and indicators. Two new bivariate distributions are presented, the Bivariate Unit-Birnbaum-Saunders distribution (BVUBS) and the Bivariate Unit-Sinh-Normal Birnbaum Saunders distribution (BVUSHN), as well as the natural effect the regression model for the case of covariates in the model, using the concept of conditionally specified distributions, these distributions are capable of modeling rates and proportions in the unit plane, and present a better fit to data compared to other distributions. Likewise, some general properties of the models, expected values and inference by maximum likelihood and application to real data are presented. The article The Multivariate Skewed Log-Birnbaum–Saunders Distribution and Its Associated Regression Model, [Martínez-Flórez et al., 2023], which focused on the multivariate extension of the Unit-Sinh-Normal Distribution, is published together with this master's thesis, studying in detail the properties of the distribution and statistical inference, a simulation study associated with the regression model and two applications with real data are included. We conclude that they are potentially useful for modeling ratio, rate or index data.MaestríaMagíster en Ciencias - EstadísticaProfundizaciónxii, 68 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ciencias - Maestría en Ciencias - EstadísticaFacultad de CienciasBogotá,ColombiaUniversidad Nacional de Colombia - Sede Bogotá510 - Matemáticas::519 - Probabilidades y matemáticas aplicadasStatistical hypothesis testingMathematical statisticsPrueba de hipótesis estadísticaEstadística matemáticaDistribución Bivariada Birnbaum Saunders unitariacondicionalmente especificadaModelo de regresión multivariadoDistibución Sinh-Normal UnitariaDatos acotadosDistribución log-Birbaum Saunders multivariadaBivariate unit-Birnbaum-Saunders distributionConditionally specifiedMultivariate regression modelUnit-Sinh-Normal distributionMultivariate log-Birnbaum Saunders distributionBounded dataDistribución Bivariada Birnbaum-Saunders UnitariaBivariate unit-Birnbaum-Saunders distributionTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAhmed, S., Castro-Kuriss, C., Leiva, V., Flores, E., and Sanhueza, A. (2010). Truncated version of the birnbaum–saunders distribution with an application in financial risk. Pakistan Journal of Statistics, 26:293–311Arnold, B., Castillo, E., and Sarabia, J. (2002). Conditionally specified multivariate skewed distributions. The Indian Journal of Statistics, 64(2):206–226. http: //www.jstor.org/stable/25051391Athayde, E. (2017). A characterization of the birnbaum–saunders distribution. REVSTAT Statistical Journal, 15:333–354Azzalini, A. (1985). A class of distributions which includes the normal ones. Scandinavian Journal of Statistics, 12(2):171–178. http://www.jstor.org/stable/ 4615982Barlow, R. and Proschan, F. (1965). Mathematical theory of reliability. Wiley, 1Barros, M., Galea, M., Gonzalez, M., and Leiva, V. (2010). Infuence diagnostics in the tobit censored response model. Stat. Methods Appl., 19:379–397. https: //doi.org/10.1007/s10260-010-0135-yBartlett, M. and Kendall, D. (1946). The statistical analysis of variance-heterogeneity and the logarithmic transformation. Journal of the Royal Statistical Society: Series B, 8(1):128–138. https://doi.org/10.2307/2983618Bebbington, M., Lai, C., and Zitikis, R. (2008). A proof of the shape of the birnbaum–saunders hazard rate function. Mathematical Scientist, 33:49–56Birnbaum, Z., Esary, J., and Marshall, A. (1966). Stochastic characterization of wear-out for components and systems. Annals of Mathematical Statistics, 37:816–825. https://www.jstor.org/stable/2238571Birnbaum, Z. W. and Saunders, S. (1969). A new family of life distributions. Journal of Applied Probability, 6(2):319–327. https://doi.org/10. 2307/3212003Cepeda Cuervo, E., Achcar, J., and Garrido Lopera, B. (2014). Bivariate beta regression models: Joint modeling of the mean, dispersion and association parameters. Journal of Applied Statistics, 41. https://doi.org/10.1080/02664763. 2013.847071Chhikara, R. and Folks, J. (1977). The inverse gaussian distribution as a lifetime model. Technometrics, 19(4):461–468. https://doi.org/10.2307/ 1267886Cook, D., Kieschnick, R., and McCullough, B. (2008). Regression analysis of proportions in finance with self selection. Journal of Empirical Finance, 15:860–867. https://doi.org/10.1016/j.jempfin.2008.02.001Desmond, A. (1985). Stochastic models of failure in random environments. Statistical Society of Canada, 13(3):171–183. https://doi.org/10.2307/3315148Davis, J. (1952). An analysis of some failure data. Journal of the American Statistical Association, 47:113–150. https://doi.org/10.2307/2280740Dupuis, D. and Mills, J. (1998). Robust estimation of the birnbaum-saunders distribution. IEEE Transactions on Reliability, 47:88–95Esary, J. and Marshall, A. (1973). Shock models and wear processes. The Annals of Probability, 1:627–649. https://www.jstor.org/stable/2959434Farias, R. and Lemonte, A. (2011). Bayesian inference for the birnbaum–saunders nonlinear regression model. Statistical Methods and Applications, 20:423–438. https://doi.org/10.1007/s10260-011-0165-0Díaz, J. and Leiva, V. (2005). A new family of life distributions based on the elliptically contoured distributions. Journal of Statistical Planning and Inference, 128:445–457. https://www.sciencedirect.com/science/article/pii/ S0378375804000072Díaz-García, J. and Domínguez-Molina, J. (2006). Some generalisations of birnbaum–saunders and sinh-normal distributions. International Mathematical Forum, 1:1709–1727. http://dx.doi.org/10.12988/imf.2006. 06146Freeman, D. (2007). Drunk driving legislation and traffic fatalities: New evidence on bac 08 laws. Contemporary Economic Policy 25, 293–308Freudenthal, A. and Shinozuka, M. (1961). Structural Safety Under Conditions of Ultimate Load Failure and Fatigue. Wright Air Development DivisionGalea, M., Leiva, V., and Paula, G. (2004). Influence diagnostics in log-birnbaum–saunders regression models. 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Technometrics, 1:389–407. https://doi.org/10.2307/1266719EstudiantesInvestigadoresMaestrosLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/83771/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL1012410876.2023.pdf1012410876.2023.pdfMaestría en Ciencias - Estadísticaapplication/pdf1745548https://repositorio.unal.edu.co/bitstream/unal/83771/2/1012410876.2023.pdfabf02bc7a5ca0319fe9c303a5af03d61MD52THUMBNAIL1012410876.2023.pdf.jpg1012410876.2023.pdf.jpgGenerated Thumbnailimage/jpeg3857https://repositorio.unal.edu.co/bitstream/unal/83771/3/1012410876.2023.pdf.jpg3213b62938c6fda0d3b0ab2c35a1092aMD53unal/83771oai:repositorio.unal.edu.co:unal/837712024-08-04 23:10:42.837Repositorio Institucional Universidad Nacional de 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