Generalized inverted exponential distribution under hybrid censoring

Dey, Sanku; Pradhan, Biswabrata

doi:10.1016/j.stamet.2013.07.007

Cited by 64 publications

(31 citation statements)

References 31 publications

(48 reference statements)

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“…Deya et al [7] indicated that Weibull distribution fits this dataset better than the exponential, inverted exponential and gamma distribution. The following dataset represents the number of millions of revolutions before failure for each of the 23 ball bearings in a life test.…”

Section: Application To Real Life Datamentioning

confidence: 86%

A Weibull failure model to the study of the hierarchical Bayesian reliability

Zhu¹,

Yan²,

Peng³

2016

EiN

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Section: Application To Real Life Datamentioning

confidence: 86%

A Weibull failure model to the study of the hierarchical Bayesian reliability

Zhu¹,

Yan²,

Peng³

2016

EiN

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“…One may also refer to Abouammoh and Table 8. Goodness-of-fit tests for different distributions Vol 14, No 2, June 2015, pp.183-195, © 2015 Alshingiti (2009), Dey and Kundu (2009) and Dey and Pradhan (2013) for various other applications of this data set. Now suppose a producer proposes a lot of ball bearing and claims that the specified median life of the ball bearings is 70 million revolutions.…”

Section: Implementation Of Sampling Plansmentioning

confidence: 99%

“…In many situations it has been suggested that this distribution provides a better fit than models like exponential, gamma, Weibull, generalized exponential and inverted exponential. We refer to Abouammoh and Alshingiti (2009), Krishna and Kumar (2013) and Dey and Pradhan (2013) for further details. Observe that mean μ of a GIE ( , ) γ λ distribution is given by The corresponding 100pth percentile, say…”

Section: Generalized Inverted Exponen-tial Distributionmentioning

confidence: 99%

Sampling Plans Based on Truncated Life Test for a Generalized Inverted Exponential Distribution

Singh¹,

Tripathi²

2015

Industrial Engineering and Management Systems

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In this paper, we propose a two-stage group acceptance sampling plan for generalized inverted exponential distribution under truncated life test. Median life is considered as a quality parameter. Design parameters are obtained to ensure that true median life is longer than a given specified life at certain level of consumer's risk and producer's risk. We also explore situations under which design parameters based on median lifetime can be used for other percentile points. Tables and specific examples are reported to explain the proposed plans. Finally a real data set is analyzed to implement the plans in practical situations and some suggestions are given.

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“…Due to the convenient structure of this distribution, GIED has been used in many application fields, for example in accelerated life testing, queue theory, modeling wind speeds etc. Recently, Dey & Pradhan (2014) studied the estimation problem of GIED under the hybrid censoring scheme. Krishna & Kumar (2014) studied reliability estimation of GIED under progressive type II censored samples.…”

Section: Introductionmentioning

confidence: 99%

Parameters Estimation for Mixed Generalized Inverted Exponential Distributions with Type-II Progressive Hybrid Censoring

Tian¹,

Yang²,

Li³

et al. 2016

HJMS

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The type-II progressive hybrid censoring scheme, which is a mixture of type-II progressive and hybrid censoring schemes, has become substantially fashionable due to its flexibility of allowing for random removals of the remaining survival units at each failure time and terminating the experiment at a pre-specified time. In the literature, this censoring scheme has been used to analyze lifetime data for general population distributions such as exponential distributions and Weibull distributions. However, we seldom focus on parameter estimations for the mixture distribution, which is an important class of models in reliability analysis. This paper aims to investigate the estimation problem of mixed generalized inverted exponential distribution (MGIED) under the type-II progressive hybrid censoring scheme. The maximum likelihood estimators (MLEs) of the model are obtained via EM algorithm. Some simulations are implemented and a case of analysis is provided to illustrate the proposed method.

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Generalized inverted exponential distribution under hybrid censoring

Cited by 64 publications

References 31 publications

A Weibull failure model to the study of the hierarchical Bayesian reliability

A Weibull failure model to the study of the hierarchical Bayesian reliability

Sampling Plans Based on Truncated Life Test for a Generalized Inverted Exponential Distribution

Parameters Estimation for Mixed Generalized Inverted Exponential Distributions with Type-II Progressive Hybrid Censoring

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