Exact inference on multiple exponential populations under a joint type-II progressive censoring scheme

Recently, the balanced joint progressive censoring (BJPC) for two samples has been introduced by the authors. This work comprises of developing testing of hypothesis for the BJPC scheme. An exact likelihood ratio test is developed to test the ratio of mean life times of two different products through joint life testing experiment. Along with this development, the Wald test has also been discussed, and an approximate power function has been used for power computation. Along with the study of testing of hypothesis, the optimal censoring scheme based on the power of the proposed tests has been determined. Meta heuristic variable neighborhood algorithm is exploited in this optimization task.

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“…In case of Wald test, for fixed m, n, k, optimal scheme will maximize the power of the Wald test derived in (8).…”

Section: Optimal Sampling Plan Based On the Power Of The Testmentioning

confidence: 99%

“…) denote the number of observed failure from Sam-2. A significant amount of work has been done on different aspects of a BJPC scheme, see for example Mondal and Kundu, 8,9 Mondal et al, 10 Prajapati et al, 11 Goel and Krishna, 12 Alfaer et al, 13 and see the references cited therein.…”

Section: Introductionmentioning

confidence: 99%

Exact likelihood ratio and Wald tests for the balanced joint progressive censoring scheme

Mondal

Kundu

2022

Appl Stoch Models Bus & Ind

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“…Ref. [ 20 ] extended it to multiple exponential populations and provided statistical inference. In the same year, they proposed a new two-sample progressively type-II censoring scheme [ 21 ] to study two populations more conveniently.…”

Section: Introductionmentioning

confidence: 99%

Statistical Inference of Inverted Exponentiated Rayleigh Distribution under Joint Progressively Type-II Censoring

Fan

Gui

2022

Entropy

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Inverted exponentiated Rayleigh distribution is a widely used and important continuous lifetime distribution, which plays a key role in lifetime research. The joint progressively type-II censoring scheme is an effective method used in the quality evaluation of products from different assembly lines. In this paper, we study the statistical inference of inverted exponentiated Rayleigh distribution based on joint progressively type-II censored data. The likelihood function and maximum likelihood estimates are obtained firstly by adopting Expectation-Maximization algorithm. Then, we calculate the observed information matrix based on the missing value principle. Bootstrap-p and Bootstrap-t methods are applied to get confidence intervals. Bayesian approaches under square loss function and linex loss function are provided respectively to derive the estimates, during which the importance sampling method is introduced. Finally, the Monte Carlo simulation and real data analysis are performed for further study.

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“…Joint censoring scheme is quite useful to conduct comparative life testing experiment of different products. Mondal and Kundu 9,10 have introduced a joint progressive censoring scheme applied on two or multiple samples called the balanced joint progressive censoring (BJPC) scheme. Here we briefly discuss the BJPC scheme on two samples.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand under certain set‐up, this joint censoring scheme, provides better estimation than conventional progressive Type‐II censoring schemes applied on two samples separately. For detail study see Mondal and Kundu 9‐11 . Due to these factors, application of the acceptance sampling plan under the BJPC scheme, can be regarded very beneficial and convenient in statistical quality control.…”

Section: Introductionmentioning

confidence: 99%

Optimal decision‐theoretic sampling plan for two exponential distributions under joint censoring scheme

Prajapati

Mondal

Kundu

2020

Appl Stoch Models Bus & Ind

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In statistical quality control, decision‐theoretic approach draws a significant amount of attention due to its economic considerations. In reliability life testing, decision‐theoretic approach has been used quite extensively under different censoring schemes. All these implementations are based on single sample of products coming from a particular source. In this work we study decision‐theoretic approach on two sample of products coming from two different sources under a joint censoring scheme when the life times are exponentially distributed. The major advantage of such implementation is to take decision on the acceptance or rejection of one or both the batches in a single life testing experiment. Decision making is performed based on minimizing the Bayes risk with respect to a given loss function. It is observed that under certain set‐ups, the joint censoring scheme is preferable over the two separate single sample censoring schemes in decision making.

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Exact inference on multiple exponential populations under a joint type-II progressive censoring scheme

Cited by 15 publications

References 15 publications

Exact likelihood ratio and Wald tests for the balanced joint progressive censoring scheme

Exact likelihood ratio and Wald tests for the balanced joint progressive censoring scheme

Statistical Inference of Inverted Exponentiated Rayleigh Distribution under Joint Progressively Type-II Censoring

Optimal decision‐theoretic sampling plan for two exponential distributions under joint censoring scheme

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