Version 1
: Received: 8 October 2023 / Approved: 9 October 2023 / Online: 9 October 2023 (10:47:21 CEST)
Version 2
: Received: 10 October 2023 / Approved: 11 October 2023 / Online: 11 October 2023 (10:32:33 CEST)
How to cite:
Taha, T. A.; Salman, A. N. Comparison Different Estimation Method for Reliability Function of Based On Fuzzy Lifetime Data. Preprints2023, 2023100481. https://doi.org/10.20944/preprints202310.0481.v2
Taha, T. A.; Salman, A. N. Comparison Different Estimation Method for Reliability Function of Based On Fuzzy Lifetime Data. Preprints 2023, 2023100481. https://doi.org/10.20944/preprints202310.0481.v2
Taha, T. A.; Salman, A. N. Comparison Different Estimation Method for Reliability Function of Based On Fuzzy Lifetime Data. Preprints2023, 2023100481. https://doi.org/10.20944/preprints202310.0481.v2
APA Style
Taha, T. A., & Salman, A. N. (2023). Comparison Different Estimation Method for Reliability Function of Based On Fuzzy Lifetime Data. Preprints. https://doi.org/10.20944/preprints202310.0481.v2
Chicago/Turabian Style
Taha, T. A. and Abbas najm Salman. 2023 "Comparison Different Estimation Method for Reliability Function of Based On Fuzzy Lifetime Data" Preprints. https://doi.org/10.20944/preprints202310.0481.v2
Abstract
In this study, we present different methods of estimating fuzzy reliability of a two-parameter Rayleigh distribution via the maximum likelihood estimator, median first-order statistics estimator, quartile estimator, L-moment estimator, and mixed Thompson-type estimator. The mean-square error MSE as a measurement for comparing the considered methods using simulation through different values for the parameters and unalike sample sizes is used. The results of simulation show that the fuzziness values are better than the real values for all sample sizes, as well as the fuzzy reliability at the estimation of the Maximum
Keywords
Topp-Leone Distributions; Stress-Strength Model; Monte Carlo simulation
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Taha Taha
Commenter's Conflict of Interests: Author