Research article

A novel Muth generalized family of distributions: Properties and applications to quality control

  • Received: 08 October 2022 Revised: 18 December 2022 Accepted: 19 December 2022 Published: 05 January 2023
  • MSC : 62E15, 62E05, 62E10

  • In this paper, we propose a novel family of distributions called the odd Muth-G distributions by using Transformed-Transformer methodology and study their essential properties. The distinctive feature of the proposed family is that it can provide numerous special models with significant applications in reliability analysis. The density of the new model is expressible in terms of linear combinations of generalized exponentials, a useful feature to extract most properties of the proposed family. Some of the structural properties are derived in the form of explicit expressions such as quantile function, moments, probability weighted moments and entropy. The model parameters are estimated following the method of maximum likelihood principle. Weibull is selected as a baseline to propose an odd Muth-Weibull distribution with some useful properties. In order to confirm that our results converge with minimized mean squared error and biases, a simulation study has been performed. Additionally, a plan acceptance sampling design is proposed in which the lifetime of an item follows an odd Muth-Weibull model by taking median lifetime as a quality parameter. Two real-life data applications are presented to establish practical usefulness of the proposed model with conclusive evidence that the model has enough flexibility to fit a wide panel of lifetime data sets.

    Citation: Ayed. R. A. Alanzi, M. Qaisar Rafique, M. H. Tahir, Farrukh Jamal, M. Adnan Hussain, Waqas Sami. A novel Muth generalized family of distributions: Properties and applications to quality control[J]. AIMS Mathematics, 2023, 8(3): 6559-6580. doi: 10.3934/math.2023331

    Related Papers:

  • In this paper, we propose a novel family of distributions called the odd Muth-G distributions by using Transformed-Transformer methodology and study their essential properties. The distinctive feature of the proposed family is that it can provide numerous special models with significant applications in reliability analysis. The density of the new model is expressible in terms of linear combinations of generalized exponentials, a useful feature to extract most properties of the proposed family. Some of the structural properties are derived in the form of explicit expressions such as quantile function, moments, probability weighted moments and entropy. The model parameters are estimated following the method of maximum likelihood principle. Weibull is selected as a baseline to propose an odd Muth-Weibull distribution with some useful properties. In order to confirm that our results converge with minimized mean squared error and biases, a simulation study has been performed. Additionally, a plan acceptance sampling design is proposed in which the lifetime of an item follows an odd Muth-Weibull model by taking median lifetime as a quality parameter. Two real-life data applications are presented to establish practical usefulness of the proposed model with conclusive evidence that the model has enough flexibility to fit a wide panel of lifetime data sets.



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    [1] L. M. Leemis, J. T. McQueston, Univariate distribution relationships, Am. Stat. 62 (2008), http://doi.org/10.1198/000313008X270448
    [2] M. R. Irshad, R. Maya, S. P. Arun, Muth distribution and estimation of a parameter using order statistics, Statistica, 81 (2021). http://doi.org/10.6092/issn.1973-2201/9432
    [3] P. Jodra, M. D. Jimenez-Gamero, M. V. Alba-Fernandez, On the Muth distribution, Math. Mod. Anal., 20 (2015), 291–310. http://doi.org/10.3846/13926292.2015.1048540
    [4] P. Jodra, H. W. Gomez, M. D. Jimenez-Gamero, M. V. Alba-Fernandez, The power muth distribution, Math. Mod. Anal., 22 (2017), 186–201. http://doi.org/10.3846/13926292.2017.1289481 doi: 10.3846/13926292.2017.1289481
    [5] M. R. Irshad, R. Maya, A. Krishna, Exponentiated power muth distribution and associated inference, J. Ind. Soc. Prob. Stat., 22 (2021), 265–302. http://doi.org/10.1007/s41096-021-00104-3 doi: 10.1007/s41096-021-00104-3
    [6] P. Jodra, M. Arshad, An intermediate muth distribution with increasing failure rate, Com. Stat. T. Meth., 51 (2021), 8310–8327. http://doi.org/10.1080/03610926.2021.1892133 doi: 10.1080/03610926.2021.1892133
    [7] C. Chesneau, V. Agiwal, Statistical theory and practice of the inverse power Muth distribution, J. Comp. Math. Data Sci., 1 (2021). http://doi.org/10.1016/j.jcmds.2021.100004
    [8] A. Alzaatreh, F. Famoye, C. Lee, A new method for generating families of continuous distributions, Metron, 71 (2013), 63–79. http://doi.org/10.1007/s40300-013-0007-y doi: 10.1007/s40300-013-0007-y
    [9] A. A. Al-Babtain, I. Elbatal, C. Chesneau, F. Jamal, The transmuted muth generated class of distributions with applications, Symmetry, 12 (2020). http://doi.org/10.3390/sym12101677
    [10] A. M. Almarashi, F. Jamal, C. Chesneau, M. Elgarhy, A new truncated muth generated family of distributions with applications, Complexity, 12 (2021). http://doi.org/10.1155/2021/1211526
    [11] M. Bourguignon, R. B. Silva, G. M. Cordeiro, The Weibull-G family of probability distributions, J. Data. Sci., 12 (2014), 53–68. http://doi.org/10.6339/JDS.2014.12(1).1210 doi: 10.6339/JDS.2014.12(1).1210
    [12] M. H. Tahir, G. M. Cordeiro, M. Alizadeh, M. Mansoor, M. Zubair, G. G. Hamedani, The odd generalized exponential family of distributions with applications, J. Stat. Dist. Appl., 2 (2015). http://doi.org/10.1186/s40488-014-0024-2
    [13] S. Khan, O. S. Balogun, M. H. Tahir, W. Almutiry, A. A. Alahmadi, An alternate generalized odd generalized exponential family with applications to premium data, Symmetry, 13 (2021). http://doi.org/10.3390/sym13112064
    [14] S. Khan, O. S. Balogun, M. H. Tahir, W. Almutiry, A. A. Alahmadi, The gamma-uniform distribution and its application, Kybernetika, 48 (2012), 16–30.
    [15] F. S. Silva, A. Percontini, E. de-Brito, M. W. Ramos, R. Venancio, G. M. Cordeiro, The odd Lindley-G family of distribution, Aust. J. Stat., 46 (2017), 65–87.
    [16] G. M. Cordeiro, H. M. Yousof, T. G. Ramires, E. M. M. Ortega, The Burr XII system of densities: Properties, regression model and applications, J. Stat. Comput. Simul., 88 (2018), 432–456.
    [17] M. Alizadeh, E. Altun, G. M. Cordeiro, M. Rasekhi, The odd power-Cauchy family of distributions: Properties, regression models and applications, J. Stat. Comput. Simul., 88 (2018), 785–807.
    [18] G. M. Cordeiro, M. Alizadeh, T. G. Ramires, E. M. M. Ortega, The generalized odd half-Cauchy family of distributions: Properties and applications, Commun. Stat. Theor. M., 46 (2018), 5685–5705.
    [19] A. S. Hassan, S. E. Hemeda, A new fmily of additive Weibull-generated distributions, Int. J. Math. Appl., 4 (2017), 151–164.
    [20] A. S. Hassan, S. G. Nassr, Power Lindley-G family of distributions, Ann. Data Sci., 6 (2019), 189–210.
    [21] S. S. Maiti, S. Pramanik, A generalized Xgamma generator family of distributions, arXiv, 2018. https://doi.org/10.48550/arXiv.1805.03892
    [22] M. H. Tahir, S. Nadarajah, Parameter induction in continuous univariate distributions: Well-established G families, An. Acad. Bras. Ciênc., 87 (2015), 539–568. http://dx.doi.org/10.1590/0001-3765201520140299 doi: 10.1590/0001-3765201520140299
    [23] M. H. Tahir, G. M. Cordeiro, Compounding of distributions: A survey and new generalized classes, J. Stat. Dist. Appl., 3 (2016). https://doi.org/10.1186/s40488-016-0052-1
    [24] R. C. Gupta, P. L. Gupta, R. D. Gupta, Modeling failure time data by Lehman alternatives, Commun. Stat. Theor. M., 27 (1998), 887–904.
    [25] G. M. Cordeiro, E. M. M. Ortega, D. C. C.Cunha, The exponentiated generalized class of distributions, J. Data. Sci., 11 (2013), 1–27.
    [26] T. M. Apostol, Mathematical analysis, Addison-Wesley Pub. Co., 1974.
    [27] D. N. P. Murthy, M. Xi, R. Jiangs, Weibull models, Wiley, Hoboken, 2004.
    [28] R. L. Smith, J. C. Naylor, A comparison of maximum likelihood and Bayesian estimators for the three-parameter Weibull distribution J. Appl. Stat., 36 (1987), 358–369.
    [29] M. Aslam, D. Kundu, C. H. Jun, M. Ahmad, Time truncated group acceptance sampling plans for generalized exponential distribution, J. Test. Eval., 39 (2011), 671–677. https://doi.org/10.1520/JTE102921 doi: 10.1520/JTE102921
    [30] K. Khan, A. Alqarni, A group acceptance sampling plan using mean lifetime as a quality parameter for inverse Weibull distribution, Adv. Appl. Stat., 649 (2020), 237–249. https://doi.org/10.17654/AS064020237 doi: 10.17654/AS064020237
    [31] A. M. Almarashi, K. Khan, C. Chesneau, F. Jamal, Group acceptance sampling plan using Marshall-Olkin Kumaraswamy exponential (MOKw-E) distribution, Processes, 9 (2021). https://doi.org/10.3390/pr9061066
    [32] M. Aslam, M. Q. Shahbaz, Economic reliability test plans using the generalized exponential distribution, J. Stat., 14 (2007), 53–60.
    [33] R. G. Srinivasa, A group acceptance sampling plans for lifetimes following a generalized exponential distribution, Stoc. Qual. Con., 24 (2009), 75–85. https://doi.org/10.1515/EQC.2009.75 doi: 10.1515/EQC.2009.75
    [34] G. S. Rao, A group acceptance sampling plans based on truncated life tests for Marshall–Olkin extended Lomax distribution, E. J. App. Stat. Anal., 3 (2009), 18–27. https://doi.org/10.1285/i20705948v3n1p18 doi: 10.1285/i20705948v3n1p18
    [35] S. Singh, Y. M. Tripathi, Acceptance sampling plans for inverse Weibull distribution based on truncated life test, Li. Cy. Rel. Saf. Eng., 6 (2017), 169–178. https://doi.org/10.1007/s41872-017-0022-8 doi: 10.1007/s41872-017-0022-8
    [36] H. S. Klakattawi, The Weibull-gamma distribution: Properties and applications, Entropy, 21 (2019), 438.
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