The Extended Kumaraswamy Generated Family: Properties, Inference and Applications in Applied Fields


Abstract


In this paper, a new Kumaraswamy generalized family is proposed. The special sub-models of the family accommodate symmetrical, left-skewed, bimodal, right-skewed unimodal, and reverse-J densities, as well as increasing, modified bathtub, decreasing, bathtub, upside down bathtub, reverse J and J shaped hazard rates. The fundamental properties of the family are derived. The maximum likelihood method and seven other methods are used for estimating the model parameters. Numerical simulations are performed to explore the performance of these estimation methods. Three real-life data sets from medicine, agriculture and engineering are fitted to illustrate the flexibility of the proposed family. The proposed family is a good alternative to the Kumaraswamy-G, beta-G, and Topp-Leone-G families.


DOI Code: 10.1285/i20705948v16n3p740

Keywords: Exponential distribution; Generating functions; Maximum likelihood; Moments; Simulation; Stochastic ordering; Weibull distribution

References


Ahsanullah, M., Shakil, M. and Kibria, B. M. G. On a generalized raised cosine

distribution: Some properties, characterizations and applications, Moroccan Journal

of Pure and Applied analysis 5, 63{85, 2019.

Alexander, C., Cordeiro, G. M., Ortega, E. M. M. and Sarabia, J. M. Generalized

beta-generated distributions, Computational Statistics and Data Analysis 56, 1880{

, 2012.26

Aljarrah, M. A., Lee, C. and Famoye, F. On generating T-X family of distributions

using quantile functions, Journal of Statistical Distributions and Applications 1, Article 2, 2014.

Alzaatreh, A., Lee, C. and Famoye, F. A new method for generating families of

continuous distributions, Metron 71, 63{79, 2013.

Alzaatreh, A., Lee, C. and Famoye, F. T-normal family of distributions: A new

approach to generalize the normal distribution, Journal of Statistical Distributions

and Applications 1, Article 16, 2014.

Alzaghal, A., Lee, C. and Famoye, F. Exponentiated T-X family of distributions with

some applications, International Journal of Probability and Statistics 2, 31{49, 2013.

Amini, M., MirMostafaee, S. M. T. K. and Ahmadi, J. Log-gamma-generated families

of distributions, Statistics 48, 913{932, 2014.

Ampadu, C. B. The tan-G family of distributions with illustration to data in the

health sciences, Physical Science and Biophysics Journal 31, 2019.

Aryal, G. R., Ortega, E. M., Hamedani, G. G. and Yousof, H. M. The Topp-Leone

generated Weibull distribution: Regression model, characterizations and applications,

International Journal of Statistics and Probability 6, 1927{7040, 2017.

Bekker, A., Roux, R. R. R. and Mostiet, P. J. A generalization of the compound

Rayleigh distribution: Using a Bayesian method on cancer survival times, Communications in Statistics{Theory and Methods 29, 1419{1433, 2007.

Bourguignon, M., Silva, R. B. and Cordeiro, G. M. The Weibull{G family of probability distributions, Journal of Data Science 12, 53{68, 2014.

Bourguignon, M., Silva, R. B., Zea, L. M. and Cordeiro, G. M. The Kumaraswamy

Pareto distribution, Journal of Statistical Theory and Applications 12, 129{144, 2013..

Chen, G. and Balakrishnan, N. A general purpose approximate goodness-of-fit test,

Journal of Quality Technology 27, 154{161, 1995.

Cordeiro, G. M., Alizadeh, M. and Ortega, E. M. M. The exponentiated half-logistic

family of distributions: Properties and applications, Journal of Probability and Statistics, Article ID 864396, 21 pages, 2014.

Cordeiro, G. M. and de Castro, M. A new family of generalized distributions, Journal

of Statistical Computation and Simulation 81, 883{893, 2011.

Cordeiro, G. M., Ortega, E. M. M. and Nadarajah, S. The Kumaraswamy Weibull

distribution with application to failure data, Journal of the Franklin Institute 347,

-{1429, 2010.

Cordeiro, G. M., Ortega, E. M. M. and da Cunha, D. C. C. The exponentiated

generalized class of distributions, Journal of Data Science 11, 1{27, 2013.

Doornik, J. A. Ox 5: An Object-Oriented Matrix Programming Language, fifth

edition, Timberlake Consultants, London, 2007.

Eugene, N., Lee, C. and Famoye, F. Beta-normal distribution and its applications,

Communications in Statistics{Theory and Methods 31, 497{512, 2002.

Fonseca, M. B. A infu^encia da fertilidade do solo e caracteriza¸c~ao da fix¸c~ao biol´ogicaElectronic Journal of Applied Statistical Analysis 27

de N2 para o crescimento de Dimorphandra wilsonii Rizz, Master’s Thesis, Federal

University of Minas Gerais, Belo Horizonte, Brazil, 2007.

Greenwood, J. A., Landwehr, J. M. and Matalas, N. C. Probability weighted moments: Definition and relation to parameters of several distributions expressable in

inverse form, Water Resources Research 15, 1049{1054, 1979.

Gupta, R. C., Gupta, P. I. and Gupta, R. D. Modeling failure time data by Lehmann

alternatives, Communications in Statistics{Theory and Methods 27, 887{904, 1998.

Gupta, R. D. and Kundu, D. Generalized exponential distribution, Australian and

New Zealand Journal of Statistics 41, 173{188, 1999.

Gupta, R. D. and Kundu, D. Generalized exponential distribution: An alternative

to Gamma and Weibull distributions, Biometrical Journal 43, 117{130, 2001.

Jones, M. C. Families of distributions arising from the distributions of order statistics, Test 13, 1{43, 2004.

Lee, C., Famoye. F. and Olumolade, O. Beta-Weibull distribution: Some properties

and applications to censored data, Journal of Modern Applied Statistical Methods 6,

{186, 2007.

Mudholkar, G. S. and Hutson, A. D. The exponentiated Weibull family: Some properties and a flood data application, Communications in Statistics{Theory and Methods

, 3059{3083, 1996.

Mudholkar, G. S. and Srivastava, D. K. Exponentiated Weibull family for analyzing

bathtub failure data, IEEE Transactions on Reliability 42, 299{302, 1993.

Mudholkar, G. S., Srivastava, D. K. and Freimer, M. The exponentiated Weibull

family: A reanalysis of the bus-motor failure data, Technometrics 37, 436{445, 1995.

Murthy, D., Xie, M. and Jiang, R. Weibull Models, Wiley, New York, 2004.

Nadarajah, S. The exponentiated exponential distribution: A survey, AStA Advances in Statistical Analysis 95, 219{251, 2011.

Nadarajah, S., Cordeiro, G. M. and Ortega, E. M. M. The Zografos-Balakrishnan{G

family of distributions: Mathematical properties and applications, Communications in

Statistics{Theory and Methods 44, 186{215, 2015.

Nadarajah, S. and Gupta, A. K. The exponentiated gamma distribution with application to drought data, Calcutta Statistical Association Bulletin 59, 29{54, 2007.

Nadarajah, S. and Kotz, S. The exponentiated-type distributions, Acta Applicandae

Mathematicae 92, 97{111, 2006.

R Development Core Team R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing (Vienna, Austria, 2009).

Risti´c, M. M. and Balakrishnan, N. The gamma-exponentiated exponential distribution, Journal of Statistical Computation and Simulation 82, 1191{1206, 2012.

Silva, R. B., Bourguignon, M., Dias, C. R. B. and Cordeiro, G. M. The compound

class of extended Weibull power series distributions, Computational Statistics and

Data Analysis 58, 352{367, 2013.

Tahir, M. H., Cordeiro, G. M., Alzaatreh, A., Zubair, M. and Mansoor, M. The28

logistic-X family of distributions and its applications, Communications in Statistics{

Theory and Methods, forthcoming, 2015.

Torabi, H. and Montazari, N. H. The gamma-uniform distribution and its application, Kybernetika 48, 16{30, 2012.

Torabi, H. and Montazari, N. H. The logistic-uniform distribution and its application, Communications in Statistics{Simulation and Computation 43, 2551{2569,2014.

Zografos, K. and Balakrishnan, N. On families of beta- and generalized gammagenerated distributions and associated inference, Statistical Methodology 6, 344{362,


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