Invariant Exponential Models Applied to Reliability Theory and Survival Analysis

Castillo, Joan del; Puig, Pedro López

doi:10.2307/2670172

Cited by 8 publications

(3 citation statements)

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“…. ; jx n Àl k j is greater or equal to 1, then the likelihood equations of the singly truncated normal distribution do not have a solution (see Castillo, 1994;Castillo & Puig, 1999). When this occurs, the maximum of the likelihood function is attained at the border of the domain of the parameters, i.e.…”

Section: Parameter Estimationmentioning

confidence: 95%

Efficiency of a Linear Combination of the Median and the Sample Mean: The Double Truncated Normal Distribution

Damilano

Puig

2004

Scandinavian J Statistics

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We characterize all symmetric location models for which a linear combination of the median and the sample mean is an asymptotically efficient estimator of the location parameter. The resulting model can be understood as a symmetrized or double truncated normal distribution. A simple algorithm to estimate the parameters is given and an application is presented. Copyright 2004 Board of the Foundation of the Scandinavian Journal of Statistics..

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Section: Parameter Estimationmentioning

confidence: 95%

Efficiency of a Linear Combination of the Median and the Sample Mean: The Double Truncated Normal Distribution

Damilano

Puig

2004

Scandinavian J Statistics

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“…Successively, this data set has been used by Keating et Al. (1990) and Del Castillo and Puig (1999a) who consider tests of exponentiality against truly specific IFR models. They reject the null hypothesis with p values of .0384 and .027 respectively.…”

Section: Examples and Discussionmentioning

confidence: 99%

Use of mean residual life in testing departures from exponentiality

Jammalamadaka

Taufer

2006

Journal of Nonparametric Statistics

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“…Several authors proposed methods for analyzing multivariate failure time data on the basis of an assumed parametric model. Namely, Lawless (1983) who emphasized on parametric methods based on distribution such as exponential and the Weibull (Basu and Chosh, 1980;Ansell and Phillips, 1989;Larson and Dinse, 1985;Mann et al, 1974;David and Mosechberger, 1978;Lawless, 1982;Cox and Oakes, 1984;Bin Daud, 1987;Andersen et al, 1993;Ibrahim, 1994;Castillo and Puig, 1999;Hosmer and Lemeshow, 1999;Kundu and Basu, 2000;Elfaki, 2004).…”

Section: Introductionmentioning

confidence: 98%

Competing risks for reliability analysis using Cox's model

Elfaki

Daud²,

Ibrahim³

et al. 2007

Engineering Computations

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PurposeCox's model with Weibull distribution and Cox's with exponential distribution are the most important models in reliability analysis. This paper seeks to show that, with a large sample size based on expectation maximization (EM) algorithm, both models give similar results.Design/methodology/approachThe parameters of the models have been estimated by method of maximum likelihood based on EM algorithm. The objective of this analysis is to fit the modification of Cox's model with Weibull distribution and Cox's with exponential distribution, examine its performance and compare their results with Crowder et al.FindingsA simulation study indicates that the parametric Cox's model with Weibull distribution gives similar results to Cox's with exponential distribution, especially for a large sample size. Also, the modification of the two models showed better results compared with Crowder et al., especially for the second causes of failure.Originality/valueA modification of the two competing risk models has mostly been applied in failure time data and simulation data. The results of the simulation study indicate that the Weibull and exponential are suitable for Cox's model as they are easy to use and it can achieve even higher accuracy compared with other distribution models.

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Invariant Exponential Models Applied to Reliability Theory and Survival Analysis

Cited by 8 publications

References 0 publications

Efficiency of a Linear Combination of the Median and the Sample Mean: The Double Truncated Normal Distribution

Efficiency of a Linear Combination of the Median and the Sample Mean: The Double Truncated Normal Distribution

Use of mean residual life in testing departures from exponentiality

Competing risks for reliability analysis using Cox's model

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