Keywords:-

Keywords: Gumbel Distribution, Fre ́chet Distribution, Survival function, T-X family.

Article Content:-

Abstract

A new four - parameter distribution generated from Gumbel - X family called the Gumbel - Frchet distribution is introduced and studied. The structural properties including ordinary and incomplete moments, quantiles and generating functions, probability weighted moments, mean deviation about mean and median, moments of residual and reversed residual life, Renyi and - entropies and order statistics are discussed in detail. The new density function can be expressed as a linear mixture of Frchet densities. The maximum likelihood method is used to estimate the model parameters. The new distribution is applied to a real data set on survival life times to establish the flexibility of the newly developed model.

References:-

References

A.Z. Afify, G.G. Hamedani, I. Ghosh, and M.E.Mead (2015). The transmuted Marshall OlkinFrechet distribution: Properties and applications. International Journal of Statistics and Probability,4(4), 132 - 184.

Afify, A.Z, Yousof, H.M, Cordeiro, G.M and Nofal, Z.M. (2016). The Weibull Frechet distribution and its applications. Journal of Applied Statistics, 43 (14), 2608 – 2626.

Al-Aqtash,R., Lee, C. and Famoye, F.(2014). Gumbel-Weibull Distribution: Properties and Applications. Journal Of Modern Applied Statistical Methods,13(2),201-225.

Alexander, C., Cordeiro, G.M., Ortega, E.M.M. and Sarabia, J.M.(2012). Generalized beta- generated distributions. Computational Statistics and Data Analysis, 56(6), 1880-1897.

Aljarrah,M.A., Lee, C. and Famoye, F.(2014). On generating T-X family of distributions using quantile functions. Journal of Statistical distributions and Applications.1(1), 2.

Alzaatreh,A., Lee,C. and Famoye, F.(2014 a).The gamma -normal distribution: Properties and applications. Computational Statistics and DataAnalysis.69,67-80

Alzaatreh,A., Lee,C. and Famoye, F.(2014 b).T - normal family of distributions: A new approach to generalize the normal distribution. Journal of Statistical distributions and Applications.1(1), 1-16.

Alzaatreh,A., Lee,C. and Famoye, F.(2013). A new method for generating families of continuous distributions.Metron,71(1),63-79

Alzaatreh,A., Lee,C. and Famoye, F.(2013). Weibull Pareto Distribution and Its Applications. Communications in Statistics-Theory and Methods,42(9),1673-1691

Alzhaghal,A.,Lee,C. and Famoye, F.(2013). Exponentiated T-X Family of Distributions with Some Applications. International Journal of Statistics and Probability.2(3),31 – 49.

Bjerkedal, T.(1960). Acquisition of resistance in guinea pigs infected with different doses of virulent tubercle bacilli, Amer.J. Hyg.,72(1),130-148.

Cooray, K.(2010) Generalized Gumbel Distribution. Journal of Applied Statistics,37(1),37-41.

Cordeiro, G M. and de Castro, M.(2011). A new family of generalized distributions. Journal of Statistical computation andSimulation,81(7),883-893.

Eugene,N., Lee, C. and Famoye, F.(2002):Beta-normal distributionnandits applications. Communications in StatisticsTheory and Methods, 31 (4), 497-512.

Johnson,N.L.,Kotz,S.andBalakrishnan,N.(1995).ContinuousUnivariateDistributions.Vol.2(2nd edition), Wiley, NewYork.

Jose,K.,K.andAlice,T.(2004).Bivariatesemi-ParetominificationProcesses.Metrika,59,(3),305- 313.

Jose, K.K., Ancy Joseph, Ristic, M.M.(2009). A Marshall Olkin Beta distribution and mini- fication process. Journal of Probability and Statistical Science,7(2),173-186.

Jose, K.K., Sebastian, R. (2013). Marshall-Olkin Morgestern bivariate Weibull distribution. Generalisation and Applications. Economic Quality Control.28(2):105-116.

Kus, C.(2007). A new lifetime distribution. Computational Statistics and Data Analysis, 51 (9), 4497- 4509.

Marshall, A.W. and Olkin,I.(1997). A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families, Biometrika, 84 (3) , 641- 652.

McDonald, J.B.(1984). Some generalized functions for the size distributions of income.Econometrica,52 (3),641 - 652.

McDonald, J. B.,Xu, Y. J(1995). A generalization of the beta distribution with application. Journal of Econometrics, 66(1-2), 133 - 152.

Merovci,F., Alizadeh, M., Hamedani, G.G.(2016). Another Generalized Transmuted Family of Distributions: Properties and Applications. Australian Journal ofStatistics.45.71-93.

Moors, J.J.A.(1998). A quantile alternative for kurtosis. The Statistician 37(1), 25-32.

Nadarajah, S., Kotz, S.(2006). The exponentiated type distributions. Acta Applicandae Mathematicae,92 (2):97-111.

Navarro,J., Franco, M. and Ruiz, J.M.(1998).Characterization through moments of the residual life and conditional spacing. Sankhya: The Indian Journal of Statistics. 60(1):36-48.

Tahir, M.H., Cordeiro, G.M., Alzaatreh, A., Mansoor, M. and Zubair, M.(2016).The Logistic-X family of distributions and its applications. Communications in Statistics-Theory and Methods, 45(24), 7326 – 7349.

Tahir, M.H., Cordeiro, G.M., Alzaatreh, A.,Mansoor, M. and Zubair, M.(2015). The Kumaraswamy Pareto IV Distribution. Australian Journal of Statistics.55, 1 – 20.

Tahir, M.H., Hussain, M.A., Cordeiro, G.M., Hamedani, G.G., Mansoor, M. and Zubair, M.(2016).The Gumbel-Lomax Distribution: Properties and Applications. Journal of Statistical Theory and Applications.15 (1),61-79.

Torabi, H. and Montazeri, N.(2014) The Logistic-Uniform Distributionandits Application. Communication in Statistics-Simulation and Computation. 43(10):2551-2569.

Torabi,H. and Montazeri, N. (2012).The Gamma-Uniform Distribution.Kybernetika,48(1),16- 30.

Zografos, K. and Balakrishnan, N. (2009). On families of beta- and generalized gamma generated distributions and associated inference. Statistical Methodology. 6(4):344-362.

Zoroa, P., Ruiz,J.M. and Martin, J.(1990).A characterization based on conditional expectations. Communication in Statistics: Theory and Methods: 19(8), 3127-3135.

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Joseph, J., & Jose, K. (2019). Gumbel - Fre ́chet Distribution and its Applications. International Journal Of Mathematics And Computer Research, 7(05), 1954-1964. https://doi.org/10.31142/ijmcr/v7i5.01