Properties of a Multivariate Survival Distribution Generated By a Weibull & Inverse-Gaussian Mixture

Lloyd R. Jaisingh; Dipak K. Dey; William S. Griffith

doi:10.1109/24.273591

Properties of a Multivariate Survival Distribution Generated By a Weibull & Inverse-Gaussian Mixture

Lloyd R. Jaisingh
, Dipak K. Dey
, William S. Griffith

Dr. Bing Zhang Department of Statistics

Producción científica: Article › revisión exhaustiva

15 Citas (Scopus)

Resumen

In this paper, we consider the influence of the work environment on a system of non-renewable components. The failure times for the components are Weibull distributed and the work environment has an inverse-Gaussian distribution. A multivariate Weibull & inverse-Gaussian mixture distribution is derived. Several pertinent properties for this multivariate distribution are discussed that shed some light on the nature of the distribution. We account for the operating environment and its changing nature by averaging over a parameter corresponding to the environment. The distribution is applied to find the mean number of components working at some mission time and the reliability for k-out-n components.

Idioma original	English
Páginas (desde-hasta)	618-622
Número de páginas	5
Publicación	IEEE Transactions on Reliability
Volumen	42
N.º	4
DOI	https://doi.org/10.1109/24.273591
Estado	Published - dic 1993

Nota bibliográfica

Funding Information:
This work was supported by the Kentucky EPSCoR Regional Universities Visiting Scholar Program, 1989. The second author’s work was supported by AOFSR, Grant No. 89-0225. We are pleased to thank the referee (unknown) for providing us with an example to illustrate lemma 3.

Financiación

This work was supported by the Kentucky EPSCoR Regional Universities Visiting Scholar Program, 1989. The second author’s work was supported by AOFSR, Grant No. 89-0225. We are pleased to thank the referee (unknown) for providing us with an example to illustrate lemma 3.

Financiadores	Número del financiador
AOFSR	89-0225
Kentucky EPSCoR Regional Universities

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Affordable and clean energy

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Electrical and Electronic Engineering

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title = "Properties of a Multivariate Survival Distribution Generated By a Weibull \& Inverse-Gaussian Mixture",

abstract = "In this paper, we consider the influence of the work environment on a system of non-renewable components. The failure times for the components are Weibull distributed and the work environment has an inverse-Gaussian distribution. A multivariate Weibull \& inverse-Gaussian mixture distribution is derived. Several pertinent properties for this multivariate distribution are discussed that shed some light on the nature of the distribution. We account for the operating environment and its changing nature by averaging over a parameter corresponding to the environment. The distribution is applied to find the mean number of components working at some mission time and the reliability for k-out-n components.",

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note = "Funding Information: This work was supported by the Kentucky EPSCoR Regional Universities Visiting Scholar Program, 1989. The second author{\textquoteright}s work was supported by AOFSR, Grant No. 89-0225. We are pleased to thank the referee (unknown) for providing us with an example to illustrate lemma 3.",

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AU - Jaisingh, Lloyd R.

AU - Dey, Dipak K.

AU - Griffith, William S.

N1 - Funding Information: This work was supported by the Kentucky EPSCoR Regional Universities Visiting Scholar Program, 1989. The second author’s work was supported by AOFSR, Grant No. 89-0225. We are pleased to thank the referee (unknown) for providing us with an example to illustrate lemma 3.

PY - 1993/12

Y1 - 1993/12

N2 - In this paper, we consider the influence of the work environment on a system of non-renewable components. The failure times for the components are Weibull distributed and the work environment has an inverse-Gaussian distribution. A multivariate Weibull & inverse-Gaussian mixture distribution is derived. Several pertinent properties for this multivariate distribution are discussed that shed some light on the nature of the distribution. We account for the operating environment and its changing nature by averaging over a parameter corresponding to the environment. The distribution is applied to find the mean number of components working at some mission time and the reliability for k-out-n components.

AB - In this paper, we consider the influence of the work environment on a system of non-renewable components. The failure times for the components are Weibull distributed and the work environment has an inverse-Gaussian distribution. A multivariate Weibull & inverse-Gaussian mixture distribution is derived. Several pertinent properties for this multivariate distribution are discussed that shed some light on the nature of the distribution. We account for the operating environment and its changing nature by averaging over a parameter corresponding to the environment. The distribution is applied to find the mean number of components working at some mission time and the reliability for k-out-n components.

KW - Environmental factor

KW - Test environment

KW - Work environment

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EP - 622

JO - IEEE Transactions on Reliability

JF - IEEE Transactions on Reliability

IS - 4

ER -

Properties of a Multivariate Survival Distribution Generated By a Weibull & Inverse-Gaussian Mixture

Resumen

Nota bibliográfica

Financiación

ODS de las Naciones Unidas

ASJC Scopus subject areas

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