Estimation of the Burr type III distribution with application in unified hybrid censored sample of fracture toughness

Panahi, Hanieh

doi:10.1080/02664763.2016.1258549

Cited by 23 publications

(12 citation statements)

References 23 publications

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“…Therefore, the Fisher information about under Type-II UHCS can be obtained by Equations (3), (8), and (9) as…”

Section: And C X R∶n ∧T 1 Denote the Expected Duration Under Type-i Hmentioning

confidence: 99%

“…When T 2 = ∞ , it reduces to generalized Type‐I hybrid censoring, and when l = 0, it reduces to generalized Type‐II hybrid censoring scheme. For some additional information on Type‐II UHCS, the interested readers may refer to previous studies 5‐9 …”

Section: Introductionmentioning

confidence: 99%

“…For some additional information on Type-II UHCS, the interested readers may refer to previous studies. [5][6][7][8][9]…”

Section: Introductionmentioning

confidence: 99%

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Statistical inference and Bayesian optimal life‐testing plans under Type‐II unified hybrid censoring scheme

Sen

Bhattacharya

Pradhan

et al. 2020

Quality & Reliability Eng

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This article describes the inferential procedures and Bayesian optimal life‐testing issues under Type‐II unified hybrid censoring scheme. First, the explicit expressions of expected number of failures, expected duration of testing, and Fisher information matrix for the unknown parameters of the underlying lifetime model are derived. Then, using these quantities, the Bayesian optimal life‐testing plans are computed in a subsequent section. A cost constraint D‐optimal optimization problem has been formulated, and the corresponding solution algorithm is provided to obtain optimal plans. Computational procedures are illustrated through numerical examples.

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“…Therefore, the Fisher information about under Type-II UHCS can be obtained by Equations (3), (8), and (9) as…”

Section: And C X R∶n ∧T 1 Denote the Expected Duration Under Type-i Hmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Statistical inference and Bayesian optimal life‐testing plans under Type‐II unified hybrid censoring scheme

Sen

Bhattacharya

Pradhan

et al. 2020

Quality & Reliability Eng

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show abstract

“…A mixture of Type I and Type II censoring schemes is known as the hybrid censoring scheme (see, [4,12,19] and [18]). These censoring schemes do not allow for removal of units at points other than the terminal point of the experiment.…”

Section: Introductionmentioning

confidence: 99%

Interval estimation of Kumaraswamy parameters based on progressively type II censored sample and record values

Panahi¹

2020

MMN

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In this paper, interval estimation for the parameters of the Kumaraswamy distribution is studied based on progressively censoring scheme and the record values. Some pivotal quantities and Theorems are proposed to construct the exact confidence interval for the one-shape parameter and the joint confidence region for the two-shape parameters. Simulation study is performed to investigate the coverage probabilities of the proposed confidence under progressively censored sample and upper record data. Finally, the proposed intervals and regions have been studied based on two real data sets as the illustrative examples. The first data set contains the strength characterization of brittle material and the second data set consists of the daily average wind speeds.

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“…To overcome these problems, Balakrishnan et al (2008) proposed a unified hybrid censoring scheme (UHCS). For more about unified hybrid censored samples, the reader is referred to Mohie El- Din et al (2017), Hasaballah (2016), Rastogi and Tripathi (2013), Balakrishnan and Kundu (2013), Habibi Rad and Izanlo (2011), Huang and Yang (2010), Panahi (2017). Although some articles have been done on the unified hybrid censoring scheme but we have not come across any article on the behavior of the two rival models under unified hybrid censoring scheme.…”

Section: Introductionmentioning

confidence: 99%

Model Selection Based on Tracking Interval under Unified Hybrid Censored Samples

Sayyareh

Panahi

2018

JIRSS

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Abstract. The aim of statistical modeling is to identify the model that most closely approximates the underlying process. Akaike information criterion (AIC) is commonly used for model selection but the precise value of AIC has no direct interpretation. In this paper we use a normalization of a difference of Akaike criteria in comparing between the two rival models under unified hybrid censoring scheme. Asymptotic properties of maximum likelihood estimator based on the missing information principle are derived. Also, asymptotic distribution of the normalized difference of AICs is obtained and it is used to construct an interval, say tracking interval, for comparing the two competing models. Monte Carlo simulations are performed to examine how the proposed interval works for different censoring schemes. Two real datasets have been analyzed for illustrative purposes. The first is selecting between Weibull and generalized exponential distributions for main component of spearmint essential oil purification data. The second is the choice between models of the lifetimes of 20 electronic components.

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Estimation of the Burr type III distribution with application in unified hybrid censored sample of fracture toughness

Cited by 23 publications

References 23 publications

Statistical inference and Bayesian optimal life‐testing plans under Type‐II unified hybrid censoring scheme

Statistical inference and Bayesian optimal life‐testing plans under Type‐II unified hybrid censoring scheme

Interval estimation of Kumaraswamy parameters based on progressively type II censored sample and record values

Model Selection Based on Tracking Interval under Unified Hybrid Censored Samples

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