Generalized Inverted Kumaraswamy Distribution Properties and Estimation | ||||
المجلة العلمية لقطاع کليات التجارة بجامعة الأزهر | ||||
Article 7, Volume 24, Issue 1, June 2020, Page 99-132 PDF (1.76 MB) | ||||
Document Type: المقالة الأصلية | ||||
DOI: 10.21608/jsfc.2020.248234 | ||||
View on SCiNiTO | ||||
Authors | ||||
Mahmoud A. A.* ; R. M. Refaey* | ||||
Statistics Department, Faculty of Commerce AL-Azhar University (Girls Branch), Cairo, Egypt | ||||
Abstract | ||||
The modeling and analysis of lifetimes is an important aspect of statistical work in awide variety of scientific and technological fields. In recent years it is observed that inverted Kumaraswamy distribution has been used quite effectively to model many lifetime data. The main objective of this researchis to construct a generalized inverted Kumaraswamy distribution based on M mixture representation. Also, this research isto develop a general form of inverted Kumaraswamy distribution which is flexible more than the inverted Kumaraswamy distribution and all of its related andsubmodules. Some properties of the generalized inverted Kumaraswamy distribution such as probability density function and cumulative distribution function are presented.The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is derived. Also, the Bayesian method is used to obtain the estimators of the parameters. A simulation study is carried out to illustrate the theoretical results of the maximum likelihood estimation and Bayesian estimation. Finally, the importance and flexibility of the new model of real data set are proved empirically. | ||||
Keywords | ||||
GeneralizedInverted Kumaraswamy Distribution; M Mixture; Maximum Likelihood Estimation; Bayesian estimation | ||||
References | ||||
Abd AL-Fattah, A. M., EL-Helbawy, A. A. and AL-Dayian, G. R. (2017). Inverted Kumaraswamy distribution: properties and estimation. Pakistan Journal of Statistics, 33(1), 37-61.
|
||||
Abd EL-Kader, R.E, AL-Dayian, G.R. and AL-Gendy, S.A. (2003). Inverted Pareto Type I distribution: properties and estimation. Journal of Faculty of Commerce AL-Azhar University, Girls’ Branch, 21, 19-40.
|
||||
AL-Dayian, G.R. (1999). Burr Type III distribution: properties and estimation. The Egyptian Statistical Journal, 43, 102-116.
|
||||
Bhaumik, D. K., Kapur, K. and Gibbons, R. D. (2009). Testing parameters of a gamma distribution for small samples. Technometrics. 51(3), 326-334. doi.org/10.1198/tech.2009.07038
|
||||
Calabria, R. and Pulcini, G. (1990). On the maximum likelihood and least squaressstimation in the inverse Weibull distribution. Journal of Statistica Applicate, 2, 3-66.
|
||||
Gupta, R. C., Gupta, P. L., and Gupta, R. D. (1998). Modeling failure time data by lehmanalternatives. Communications in Statistics-Theory and Methods, 27(4), 887-904.
Iqbal, Z., Tahir, M., M., Riaz, N., Ali, S., A. and Ahmad, M. (2017). Generalize inverted Kumaraswamy distribution properties and applications.Open Journal of Statistics, Vol. 7, pp. 645-662.
|
||||
Kumaraswamy, P. (1980). A Generalized probability density function for doublebounded random processes. Journal of Hydrology, 46, 79-88.
Mohie El-Din, M. and Abu-Moussa, M. (2018).On estimation and prediction for the inverted Kumaraswamy distribution based on general progressive censored samples. Pakistan Journal of Statisticsand Operation Research,Vol. 14, pp. 717-736.
|
||||
Mudholkar, G. S., Sriastava, D. K. and Freimer, M. (1995). The exponentiated Weibull family: a reanalysis of the bus motor failure data. Technimetrics, 37, 436-445.
|
||||
Prakash, G. (2012). Inverted exponential distribution under a Bayesian view point. Journal of Modern Applied Statistical Methods, 11, 190-202.
Usman, R., M. and Haq, M., A. (2018). The Marshall-Olkin extended inverted Kumaraswamy distribution theory and applications.Journal of King Saud University – Science,https://doi.org/10.1016/j.jksus.2018.05.0.
|