Progressive stress accelerated life tests under finite mixture models

Abdel-Hamid, Alaa H.; AL-Hussaini, Essam K.

doi:10.1007/s00184-006-0106-3

Cited by 44 publications

(22 citation statements)

References 15 publications

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“…In Step-Stress PALT, a test item is run first at normal use condition and, if it does not fail, then it is run at accelerated condition until failure occurs or the observation is censored. Several references have with SS-PALT, a little few of them are [13], [14], [15], [16], [17], [18] and [19].…”

Section: Step-stress Partially Accelerated Life Tests (Ss-palt)mentioning

confidence: 99%

Bound lengths for Burr-XII distribution under step-stress PALT

Prakash

2017

Int. J. Sci. World

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Some inferences based on Step-Stress Partially Accelerated Life Test (SS-PALT) are discussed in the present article. The Progressive Type-II censoring criterion with Random Removal scheme is used for determining the Approximate Confidence Lengths and One-Sample Bayes Prediction Bound Lengths for the unknown parameters of the Burr Type-XII distribution. Based on the simulated data, the analysis of the present discussion has been carried out.

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Section: Step-stress Partially Accelerated Life Tests (Ss-palt)mentioning

confidence: 99%

Bound lengths for Burr-XII distribution under step-stress PALT

Prakash

2017

Int. J. Sci. World

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“…See [1,11,12]. It may be remarked that distributions, defined over the whole real line may be represented by (1) with the appropriate choice of u j (t).…”

Section: Introductionmentioning

confidence: 99%

Prediction for Progressively Type-II Censored Competing Risks Data from the Half-Logistic Distribution

AL-Hussaini¹,

Abdel-Hamid²,

Hashem³

2020

JSTA

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Point and interval predictions of the s-th order statistic in a future sample are discussed. The informative sample is assumed to be drawn from a general class of distributions which includes, among others, Weibull, compound Weibull, Pareto, Gompertz and half-logistic distributions. The informative and future samples are progressively type-II censored, under competing risks model, and assumed to be obtained from the same population. A special attention is paid to the half-logistic distribution. Using six different progressive censoring schemes, numerical computations are carried out to illustrate the performance of the procedure. An illustrative example based on real data is also considered. The biases, mean squared prediction errors of the maximum likelihood predictors, coverage probabilities and average interval lengths of the Bayesian prediction intervals are computed via a simulation study.

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“…The first method is called the constant stress ALT; the stress is kept at a constant level throughout the life of test products, (see for example [2] [3] [4] [5]). The second one is referred to as progressive stress ALT; the stress applied to a test product is continuously increasing in time (see for example, [6] [7] [8]). …”

Section: Introductionmentioning

confidence: 99%

“…[4] [5] used a finite mixture model to study the effect of a constant stress on the parameters, reliability and hazard rate functions. [8] considers the progressive stress ALT applied to a product whose lifetime under design condition is assumed to follow a mixture of k components each of which represents a different cause of failure.…”

Section: Introductionmentioning

confidence: 99%

Inference on Constant-Partially Accelerated Life Tests for Mixture of Pareto Distributions under Progressive Type-II Censoring

Abushal¹,

AL-Zaydi²

2017

OJS

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The main purpose of this paper is to obtain the inference of parameters of heterogeneous population represented by finite mixture of two Pareto (MTP) distributions of the second kind. The constant-partially accelerated life tests are applied based on progressively type-II censored samples. The maximum likelihood estimates (MLEs) for the considered parameters are obtained by solving the likelihood equations of the model parameters numerically. The Bayes estimators are obtained by using Markov chain Monte Carlo algorithm under the balanced squared error loss function. Based on Monte Carlo simulation, Bayes estimators are compared with their corresponding maximum likelihood estimators. The two-sample prediction technique is considered to derive Bayesian prediction bounds for future order statistics based on progressively type-II censored informative samples obtained from constant-partially accelerated life testing models. The informative and future samples are assumed to be obtained from the same population. The coverage probabilities and the average interval lengths of the confidence intervals are computed via a Monte Carlo simulation to investigate the procedure of the prediction intervals. Analysis of a simulated data set has also been presented for illustrative purposes. Finally, comparisons are made between Bayesian and maximum likelihood estimators via a Monte Carlo simulation study.

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Progressive stress accelerated life tests under finite mixture models

Abstract: Finite mixtures, Accelerated life tests, Progressive stress, Cumulative exposure model, Type-I censoring, Maximum likelihood estimation, Local Fisher information matrix, Simulation,

Cited by 44 publications

References 15 publications

Bound lengths for Burr-XII distribution under step-stress PALT

Bound lengths for Burr-XII distribution under step-stress PALT

Prediction for Progressively Type-II Censored Competing Risks Data from the Half-Logistic Distribution

Inference on Constant-Partially Accelerated Life Tests for Mixture of Pareto Distributions under Progressive Type-II Censoring

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