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Abdus Saboor, Muhammad Khan, G. Cordeiro, Marcelino Pascoa, Juliano Bortolini, S. Mubeen (2018)
Modified beta modified-Weibull distributionComputational Statistics, 34
A. Ahmad, M. Ghazal (2020)
Exponentiated additive Weibull distributionReliab. Eng. Syst. Saf., 193
A. Afify, Z. Nofal, Nadeem Butt (2014)
Transmuted Complementary Weibull Geometric DistributionPakistan Journal of Statistics and Operation Research, 10
R. Earnshaw, D. Kasik (2019)
Data Science and Visual ComputingData Science and Visual Computing
S. Dey, T. Dey, Sajid Ali, M. Mulekar (2016)
Two-parameter Maxwell distribution: Properties and different methods of estimationJournal of Statistical Theory and Practice, 10
M. Xie, Y. Tang, T. Goh (2002)
A modified Weibull extension with bathtub-shaped failure rate functionReliab. Eng. Syst. Saf., 76
G. Mudholkar, D. Srivastava, Georgia Kollia (1996)
A Generalization of the Weibull Distribution with Application to the Analysis of Survival DataJournal of the American Statistical Association, 91
W. Weibull (1951)
A Statistical Distribution Function of Wide ApplicabilityJournal of Applied Mechanics, 18
Abdus Saboor, H. Bakouch, Muhammad Khan (2016)
Beta Sarhan–Zaindin modified Weibull distributionApplied Mathematical Modelling, 40
A. Sarhan, J. Apaloo (2013)
Exponentiated modified Weibull extension distributionReliab. Eng. Syst. Saf., 112
G. Cordeiro, A. Gomes, C. da-Silva, E. Ortega (2013)
The beta exponentiated Weibull distributionJournal of Statistical Computation and Simulation, 83
A. Afify, G. Cordeiro, E. Ortega, H. Yousof, Nadeem Butt (2018)
The four-parameter Burr XII distribution: Properties, regression model, and applicationsCommunications in Statistics - Theory and Methods, 47
G. Mudholkar, D. Srivastava (1993)
Exponentiated Weibull family for analyzing bathtub failure-rate dataIEEE Transactions on Reliability, 42
M. Rahman, B. Al-Zahrani, M. Shahbaz (2019)
Cubic Transmuted Weibull Distribution: Properties and ApplicationsAnnals of Data Science, 6
(2004)
Weibull models. Wiley, Hoboken Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations
G. Silva, E. Ortega, G. Cordeiro (2010)
The beta modified Weibull distributionLifetime Data Analysis, 16
M. Bebbington, C. Lai, R. Zitikis (2007)
A flexible Weibull extensionReliab. Eng. Syst. Saf., 92
A. Ishaq, A. Abiodun (2020)
The Maxwell–Weibull Distribution in Modeling Lifetime DatasetsAnnals of Data Science
A. El-Gohary, A. El-Bassiouny, M. El-Morshedy (2015)
Inverse Flexible Weibull Extension DistributionInternational Journal of Computer Applications, 115
S. Nadarajah, M. Teimouri, S. Shih (2014)
Modified Beta DistributionsSankhya B, 76
Neetu Singla, Kanchan Jain, Suresh Sharma (2012)
The Beta Generalized Weibull distribution: Properties and applicationsReliab. Eng. Syst. Saf., 102
K. Xu, M. Xie, L. Tang, Siu Ho (2003)
Application of neural networks in forecasting engine systems reliabilityAppl. Soft Comput., 2
E. Almetwally, H. Muhammed, E. El-Sherpieny (2020)
Bivariate Weibull Distribution: Properties and Different Methods of EstimationAnnals of Data Science, 7
R. Barlow, Rafael Campo (1975)
Total time on test processes and applications to failure data
C. Quesenberry, C. Hales (1980)
Concentration bands for uniformity plotsJournal of Statistical Computation and Simulation, 11
M. Aarset (1987)
How to Identify a Bathtub Hazard RateIEEE Transactions on Reliability, R-36
Zubair Ahmad, Z. Hussain (2017)
The New Extended Flexible Weibull Distribution and Its ApplicationsJournal of data science, 3
M. El-Morshedy, A. El-Bassiouny, A. El-Gohary (2017)
Exponentiated Inverse Flexible Weibull Extension DistributionJournal of Statistics Applications & Probability, 6
Carl Lee, F. Famoye, Olugbenga Olumolade (2007)
Beta-Weibull Distribution: Some Properties and Applications to Censored DataJournal of Modern Applied Statistical Methods, 6
In this article, a new five parameter distribution, known as the modified beta flexible Weibull extension distribution, is derived and studied. Several properties of the distribution including the quantile function, moments, moment generating function, entropies and order statistics are derived. The density function and hazard rate function plots for different parameter values are obtained. It is observed that the density function plots of the distribution exhibit varying shapes and degrees of kurtosis. Also, the hazard rate function plots exhibit different shapes including decreasing, increasing, bathtub, J and reserved J shapes. The parameter estimators of the distribution are obtained using maximum likelihood estimation. The estimators are found to be consistent via a simulation study. Finally, three data sets are used to assess the usefulness of the distribution. It is observed that the distribution can serve as an alternative to modelling failure time data with different characteristics.
Annals of Data Science – Springer Journals
Published: Jun 1, 2023
Keywords: Flexible Weibull distribution; Modified beta distributions; Hazard rate function; Quantile function; Maximum likelihood estimation; Failure time
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