BAYESIAN PARAMETER ESTIMATION OF WEIBULL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR RANDOM CENSORING TEST MODEL WITH INCOMPLETE INFORMATION: Fid-Bau Portal

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BAYESIAN PARAMETER ESTIMATION OF WEIBULL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR RANDOM CENSORING TEST MODEL WITH INCOMPLETE INFORMATION

HE ChaoBing

The complete-data likelihood function of Weibull distribution with multiple change points for IIRCT is obtained by filling in missing life data using inverse transformation method. The full conditional distributions of change-point positions and other unknown parameters are obtained. Every parameter is sampled by Gibbs sampler. and the means of Gibbs samples are taken as Bayesian estimations of the parameters. The concrete steps of MCMC methods are given. The random simulation results show that the estimations are fairly accurate and the effect is good.

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BAYESIAN PARAMETER ESTIMATION OF WEIBULL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR RANDOM CENSORING TEST MODEL WITH INCOMPLETE INFORMATION

HE ChaoBing

The complete-data likelihood function of Weibull distribution with multiple change points for IIRCT is obtained by filling in missing life data using inverse transformation method. The full conditional distributions of change-point positions and other unknown parameters are obtained. Every parameter is sampled by Gibbs sampler. and the means of Gibbs samples are taken as Bayesian estimations of the parameters. The concrete steps of MCMC methods are given. The random simulation results show that the estimations are fairly accurate and the effect is good.

BAYESIAN PARAMETER ESTIMATION OF WEIBULL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR RANDOM CENSORING TEST MODEL WITH INCOMPLETE INFORMATION

HE ChaoBing

The complete-data likelihood function of Weibull distribution with multiple change points for IIRCT is obtained by filling in missing life data using inverse transformation method. The full conditional distributions of change-point positions and other unknown parameters are obtained. Every parameter is sampled by Gibbs sampler. and the means of Gibbs samples are taken as Bayesian estimations of the parameters. The concrete steps of MCMC methods are given. The random simulation results show that the estimations are fairly accurate and the effect is good.

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Titel:

BAYESIAN PARAMETER ESTIMATION OF WEIBULL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR RANDOM CENSORING TEST MODEL WITH INCOMPLETE INFORMATION

Beteiligte:

HE ChaoBing (Autor:in)

Erschienen in:

Jixie qiangdu, Vol 38, Pp 522-525 (2016)

Erscheinungsdatum:

2016

ISSN:

Medientyp:

Aufsatz (Zeitschrift)

Format:

Elektronische Ressource

Sprache:

Unbekannt

Schlagwörter:

Complete-data likelihood function , Full conditional distribution , MCMC method , Gibbs sampling , Metropolis-Hastings algorithm , Mechanical engineering and machinery , TJ1-1570 , Materials of engineering and construction. Mechanics of materials , TA401-492

Metadata by DOAJ is licensed under CC BY-SA 1.0

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