A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation

Nagahara, Yuichi

doi:10.1016/j.csda.2003.10.008

Cited by 42 publications

(41 citation statements)

References 19 publications

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“…According to Nagahara (2004), the maximum likelihood method is superior to the method of moments. In this paper, we adopt the maximum likelihood method in order to fit the financial data to the multivariate nonnormal distribution.…”

Section: Multivariate Nonnormal Distributionsmentioning

confidence: 98%

“…with e i being the ith column unit, and E ii = e i e j (see Nagahara 2004Nagahara , 2006a. According to Nagahara (2004), the maximum likelihood method is superior to the method of moments.…”

Section: Multivariate Nonnormal Distributionsmentioning

confidence: 99%

“…According to Nagahara (2004Nagahara ( , 2006a, the multivariate nonnormal distributions are constructed by the following methods; ξ 1 , . .…”

Section: Multivariate Nonnormal Distributionsmentioning

confidence: 99%

“…Such distributions are strongly requested by the area of multivariate analysis and statistical modeling. Nagahara (2004) introduced the approach based on random numbers for constructing the multivariate nonnormal distributions by not only the method of moments but also the maximum likelihood method. And it was shown that the maximum likelihood method is superior to the method of moments.…”

Section: Introductionmentioning

confidence: 99%

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A Method of Calculating the Downside Risk by Multivariate Nonnormal Distributions

Nagahara

2008

Asia-Pac Financ Markets

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Section: Multivariate Nonnormal Distributionsmentioning

confidence: 98%

Section: Multivariate Nonnormal Distributionsmentioning

confidence: 99%

“…According to Nagahara (2004Nagahara ( , 2006a, the multivariate nonnormal distributions are constructed by the following methods; ξ 1 , . .…”

Section: Multivariate Nonnormal Distributionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Method of Calculating the Downside Risk by Multivariate Nonnormal Distributions

Nagahara

2008

Asia-Pac Financ Markets

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“…Once a closed-form of the desired distribution is chosen and its statistical moments are set to resemble realistic AA series, random series following this distribution can be computed from uniform random series, as described by Devroye [132] and Nagahara [133]. This process is illustrated in Fig.…”

Section: Methodology For Generating Atrial To Atrial Interval Seriesmentioning

confidence: 99%

Characterization and Modeling of Atrioventricular Conduction during Atrial Fibrillation

Climent¹,

Andreu²

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AgradecimientosLa consecución de la presente tesis hubiese sido completamente imposible sin la colaboración de numerosas personas que me han ayudado, enseñado y apoyado durante estos años. Quiero empezar agradeciendo el apoyo recibido por todos los integrantes del grupo de Bioingeniería del instituto ITACA de la Universidad Politécnica de Valencia desde que empecé a colaborar con ellos en 2005. De todos los que durante este tiempo han pasado por el laboratorio he aprendido muchísimo y tengo un más que grato recuerdo: Jose Luis Espí, José Laparra, Jose Antonio Belloch, Laura Maestro, Vicky Donis, Cinta Barber, Amparo Pomar, María Mozo, Lola Guerrero, Lydia Dux, Martina Srutova, Pietro Bonizzi, Lorena Rausell, Jesús Vila y Xavier Ibáñez. Y por supuesto quiero mandar un caluroso agradecimiento a todos con los que sigo trabajando día a día y de los que cada día aprendo nuevas cosas: Jorge Pedrón, Alejandro Liberos, Eduard Roses, Toni Guill, Alvaro Tormos, José Antonio Pérez, Toni Cebrián, Paco Castells, Conrado Calvo, Amador Ayala, María Vinaches, Cristina Rojas, Adolfo Fonseca, Jesús Escrivá y Miguel Rodrigo. Comentario a parte merece José Millet del cual he aprendido innombrables cosas y cuyo espíritu entusiasta y su capacidad de encajar los problemas con tranquilidad son virtudes que querría tener la capacidad de imitar y que me acompañasen durante el resto de mi carrera.Además del apoyo de todos los compañeros del laboratorio, la realización de las diversas estancias de investigación ha sido imprescindible para que esta tesis haya llegado a buen término. Junto con el Dr. Andreas Bollmann entré en el mundo de la ciencia, deél aprendí algunas de las lecciones más valiosas entre las que quiero destacar elímpetu por colaborar y aprender siempre con los mejores estuviesen en el laboratorio de al lado o a 5000km. Este afán por conseguir enriquecer nuestras investigaciones con el apoyo de algunos de los más reputados expertos del mundo me ha llevado a Milán junto con a la Dra. Valentina Corino y al Dr. Luca Mainardi, a Suecia con los Drs. Martin Stridth y Leif Srnmo, a Cleveland junto con los Drs. Youhua Zhang y Todor Mazgalev y a Michigan junto con los Drs. Omer Berenfeld y José Jalife. Cada una de esas estancias me ha enriquecido no sólo como investigador sino como persona. Poder colaborar con investigadores tan reputados a la vez que grandes personas ha sido un regalo que es difícil de describir en unas pocas palabras pero que viajará i ii AGRADECIMIENTOS conmigo el resto de mi vida. Junto con las colaboraciones internacionales, en mi por ahora corta carrera como investigador he tenido la suerte de trabajar con grandes investigadores españoles entre los que quiero destacar a los Drs. Felipe Atienza, Aurelio Quesada y Javier Chorro por confiar en nosotros pese a nuestra juventud, ayudarnos con nuestras limitaciones y descubrirnos la parte más humana de la práctica clínica y la investigación.En el futuro, ojalá tenga la suerte de poder seguir contando con la colaboración de todos estos magníficos científicos y espero ...

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Goodness‐of‐fit measures based on the Mellin transform for beta generalized lifetime data

Vasconcelos

Cintra

Nascimento

2021

Math Methods in App Sciences

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In recent years various probability models have been proposed for describing lifetime data. Increasing model flexibility is often sought as a means to better describe asymmetric and heavy tail distributions. Such extensions were pioneered by the beta-G family. However, efficient (GoF) measures for the beta-G distributions are sought. In this paper, we combine probability weighted moments (PWMs) and the Mellin transform (MT) in order to furnish new qualitative and quantitative GoF tools for model selection within the beta-G class. We derive PWMs for the Fréchet and Kumaraswamy distributions, and we provide expressions for the MT, and for the log-cumulants (LC) of the beta-Weibull, beta-Fréchet, beta-Kumaraswamy, and beta-log-logistic distributions. Subsequently, we construct LC diagrams and, based on the Hotelling's T 2 statistic, we derive confidence ellipses for the LCs. Finally, the proposed GoF measures are applied on five real data sets in order to demonstrate their applicability.

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A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation

Cited by 42 publications

References 19 publications

A Method of Calculating the Downside Risk by Multivariate Nonnormal Distributions

A Method of Calculating the Downside Risk by Multivariate Nonnormal Distributions

Characterization and Modeling of Atrioventricular Conduction during Atrial Fibrillation

Goodness‐of‐fit measures based on the Mellin transform for beta generalized lifetime data

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