Bayesian Inference for Masked System Lifetime Data

Reiser, Benjamin; Guttman, Irwin; Lin, Dennis K.J.; Guess, Frank M.; Usher, John S.

doi:10.2307/2986196

Cited by 69 publications

(29 citation statements)

References 7 publications

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“…Goetghebeur and Ryan [17] addressed the problem of assessing covariate effects based on a semi-parametric proportional hazards structure for each failure type when the failure type is unknown for some individuals. Reiser et al [18] considered statistical procedures for analysing masked data, but their procedure Downloaded by [University of Colorado -Health Science Library] at 14:02 30 September 2014 could not be applied when all observations have an unknown cause of failure. Our model can be derived as follows.…”

Section: The Cwg Distributionmentioning

confidence: 99%

The complementary Weibull geometric distribution

Tojeiro

Louzada

Roman

et al. 2012

Journal of Statistical Computation and Simulation

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In this paper, we proposed a new three-parameters lifetime distribution with unimodal, increasing and decreasing hazard rate. The new distribution, the complementary Weibull geometric (CWG), is complementary to the Weibull-geometric (WG) model proposed by Barreto-Souza et al. (The Weibull-Geometric distribution, J. Statist. Comput. Simul. 1 (2010), pp. 1-13). The CWG distribution arises on a latent complementary risks scenarios, where the lifetime associated with a particular risk is not observable, rather we observe only the maximum lifetime value among all risks. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulas for its reliability and hazard rate functions, moments, density of order statistics and their moments. We provide expressions for the Rényi and Shannon entropies. The parameter estimation is based on the usual maximum likelihood approach. We obtain the observed information matrix and discuss inferences issues. We report a hazard function comparison study between the WG distribution and our complementary one. The flexibility and potentiality of the new distribution is illustrated by means of three real dataset, where we also made a comparison between Weibull, WG and CWG modelling approach.

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Section: The Cwg Distributionmentioning

confidence: 99%

The complementary Weibull geometric distribution

Tojeiro

Louzada

Roman

et al. 2012

Journal of Statistical Computation and Simulation

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“…Real examples of RMCR data in the reliability context and medical research can be found in Dinse (1982), Reiser et al (1995), and Flehinger et al (2001). Sen et al (2001) and Flehinger et al (2001).…”

Section: Background On Rmcr Datamentioning

confidence: 99%

Random partition masking model for censored and masked competing risks data

Wong

Qin

et al. 2010

Ann Inst Stat Math

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We consider the parametric estimation with right-censored competing risks data and with masked failure cause. We propose a new model, called the random partition masking (RPM) model. The existing model based on the so called symmetry assumption, but the RPM model does not need the symmetry assumption. We propose a wide class of parametric distribution families of the failure time and cause, which does not need the assumption of independence between the components of the system. We also study the asymptotic properties of the maximum likelihood estimator under the new model, and apply our procedure to a medical and an industrial data sets.

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“…In engineering applications, one frequently encounters data where the cause of failure is not completely known (see Reiser et al 1995;Reiser, Flehinger, and Conn 1996). In reliability literature, such data are termed as masked failure data.…”

Section: Inference From Data With Missing Cause Of Failurementioning

confidence: 99%

Statistical Inference for Power-Law Process With Competing Risks

Somboonsavatdee

Sen

2015

Technometrics

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The focus of this article is on failure history of a repairable system for which the relevant data comprise successive event times for a recurrent phenomenon along with an event-count indicator. We undertake an investigation for analyzing failures from repairable systems that are subject to multiple failure modes. Failure data representing a cluster of recurrent events from a single system are studied under the parametric framework of a power-law process, a model that has found considerable attention in industrial applications. Some interesting and nonstandard asymptotic results ensue in this context that are discussed in detail. Extensive simulation has been carried out that supplements the theoretical findings. An extension to the case where the specific cause of failure may be missing is investigated in detail. The methodology has been implemented on recurrent failure data obtained from a warranty claim database for a fleet of automobiles. Supplementary material for this article is available online.

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Bayesian Inference for Masked System Lifetime Data

Cited by 69 publications

References 7 publications

The complementary Weibull geometric distribution

The complementary Weibull geometric distribution

Random partition masking model for censored and masked competing risks data

Statistical Inference for Power-Law Process With Competing Risks

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