Estimation of parameters of inverse Weibull distribution and application to multi-component stress-strength model

Jana, Nabakumar; Bera, Samadrita

doi:10.1080/02664763.2020.1803815

Cited by 9 publications

(4 citation statements)

References 32 publications

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“…Proof. The proof follows completely similarly to the problem of existence and uniqueness of the MLE discussed by Balakrishnan and Kateri [8] and Jana and Bera [20].…”

Section: Theoremmentioning

confidence: 83%

“…Table 5 shows the maximum flood levels in millions of cubic feet per second of the Susquehanna River at Harrisburg, Pennsylvania, over 20 years from 1890 to 1969. Maswadah [24] and Jana and Bera [20] analyzed this data set using the IW model. Here we compare the MLE and MMLE to estimate the IW parameters.…”

Section: Maximum Flood Levels Of the Susquehenna Rivermentioning

confidence: 99%

“…Table 7 reports the duration of remission achieved with a drug used to treat 20 leukemia patients. See Wu and Wu [25] and Jana and Bera [20] for more details. Here we investigate whether the considered data set can be fitted to the IW model.…”

Section: Duration Of Remission Achieved By a Drugmentioning

confidence: 99%

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Modified Maximum Likelihood Estimation of the Inverse Weibull Model

Kayid,

Alshehri

2023

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The inverse Weibull model is a simple and flexible model used for survival analysis, reliability theory, and other scientific fields. The main problem in this context is the estimation of the model parameters. In this study, a modified version of the maximum likelihood estimator is presented. The idea behind it is that the likelihood equation for the shape parameters of the model is biased; therefore, an unbiased version was defined. The new estimator is based on the definition of an unbiased likelihood equation. Simulation results show that the new modified estimator for the shape parameter has a smaller mean square error. Finally, the proposed estimator and the maximum likelihood estimator were compared in the analysis of the three real data sets.

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“…Proof. The proof follows completely similarly to the problem of existence and uniqueness of the MLE discussed by Balakrishnan and Kateri [8] and Jana and Bera [20].…”

Section: Theoremmentioning

confidence: 83%

Section: Maximum Flood Levels Of the Susquehenna Rivermentioning

confidence: 99%

See 1 more Smart Citation

Modified Maximum Likelihood Estimation of the Inverse Weibull Model

Kayid,

Alshehri

2023

Axioms

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“…Alshaikh and Baklizi [8] investigated maximum likelihood estimation in the context of the inverse Weibull distribution with type II censored data. Jana and Bera [31] explored the estimation of parameters in the IWD and its application to a multi-component stress-strength model. The DUSneutrosophic multivariate IWD was recently studied by Hassan and Aslam [28].…”

Section: Review Of Related Literaturementioning

confidence: 99%

Bayesian inference for the inverse Weibull distribution based on symmetric and asymmetric balanced loss functions with application

Hasaballah,

A. Tashkandy,

Balogun

et al. 2024

Eksploatacja i Niezawodność – Maintenance and Reliability

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In this study, the unified hybrid censored approach is employed to estimate the parameters of the inverse Weibull distribution, as well as the survival and hazard rate functions. Parameter estimates are obtained using both Bayesian and Maximum Likelihood approaches, with Bayesian estimates acquired through Lindley's approximation method using three distinct balanced loss functions. These encompass both symmetric and asymmetric balanced loss functions, specifically the balanced squared error (BSE) loss function, the balanced linear exponential (BLINEX) loss function, and the balanced general entropy (BGE) loss function. We conduct a simulation study to compare the effectiveness of various estimators, and a real-world data analysis is presented to illustrate practical implementation. Ultimately, our findings indicate that Bayesian parameter estimates consistently outperform their Maximum Likelihood counterparts across all methods.

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