Gerçek Veri Uygulamaları ile Log Exponential-Power Dağılımı için Parametre Tahmin Prosedürleri

Bu makalede, log exponential-power dağılımının iki parametresini tahmin etmek için çeşitli tahmin yöntemleri araştırılmıştır. En çok olabilirlik, kuantil, en küçük kareler, ağırlıklandırılmış en küçük kareler, Anderson-Darling ve Cramer-von Mises tahmin yöntemleri detaylı olarak incelenmiştir. Bu tahmin edicilerin performanslarını değerlendirmek için Monte Carlo simülasyon deneyleri yapılmıştır. Ayrıca dört gerçek veri uygulaması gerçekleştirilmiş ve tüm tahmin ediciler Kolmogorov-Smirnov istatistiği sonuçları sunulmuştur.

Parameter Estimation Procedures for Log Exponential-Power Distribution with Real Data Applications

In this study, some estimation techniques are investigated to estimate two parameters of the log exponential-power distribution. The maximum likelihood, quantile, least squares, weighted least squares, Anderson-Darling, and Cramer-von Mises estimation methods are studied in detail. The efficiency of these estimators is validated through Monte Carlo simulation experiments. Also, four real data applications are performed and Kolmogorov-Smirnov statistic results for all estimators are presented.

___

  • Korkmaz, M.Ç., Altun, E., Alizadeh, M., El-Morshedy, M., The Log Exponential- Power Distribution: Properties, Estimations and Quantile Regression Model, Mathematics, 9 (21), 2634, 2021.
  • Smith, R.M., Bain, L.J., An exponential power life-testing distribution, Communication in Statistics Theory Methods, 4, 469–481, 1975.
  • Kumaraswamy, P., A generalized probability density function for double-bounded random processes, Journal of Hydrology, 46, 79–88, 1980.
  • Kao, J.H., Computer methods for estimating Weibull parameters in reliability studies, IRE Transactions on Reliability and Quality Control, 13, 15-22, 1958.
  • Dumonceaux, R., Antle, C.E., Discrimination between the log-normal and the Weibull distributions, Technometrics, 15 (4), 923-926, 1973.
  • Balakrishnan, N., Cohen, A.C., Order Statistics & Inference: Estimation Methods, Elsevier, Amsterdam, The Netherlands, 2014.
  • Alizadeh, M., Altun, E., Cordeiro, G.M., Rasekhi, M., The odd power Cauchy family of distributions: Properties, regression models and applications, Journal of Statistical Computation and Simulation, 88, 785–807, 2018.
  • Elgarhy, M., Exponentiated generalized Kumaraswamy distribution with applications, Annals of Data Science, 5 (2), 273-292, 2018.
  • Cordeiro, G.M., dos Santos Brito, R., The beta power distribution, Brazilian Journal Of Probability And Statistics, 26 (1), 88-112, 2012.
  • Opone, F., Iwerumor, B., A new Marshall-Olkin extended family of distributions with bounded support, Gazi University Journal of Science, 34 (3), 899-914, 2021.
  • Balogun, O.S., Iqbal, M.Z., Arshad, M.Z., Afify, A.Z., Oguntunde, P.E., A new generalization of Lehmann type-II distribution: Theory, simulation, and applications to survival and failure rate data, Scientific African, 12, e00790, 2021.
  • Saraçoğlu, B., Tanış, C., A new statistical distribution: cubic rank transmuted Kumaraswamy distribution and its properties, Journal of the National Science Foundation of Sri Lanka, 46 (4), 505-518, 2018.
  • Jamal, F., Chesneau, C., A new family of polyno-expo-trigonometric distributions with applications, Infinite Dimensional Analysis, Quantum Probability and Related Topics, 22 (04), 1950027, 2019.
Adıyaman Üniversitesi Fen Bilimleri Dergisi-Cover
  • Yayın Aralığı: Yılda 2 Sayı
  • Başlangıç: 2011
  • Yayıncı: Adıyaman Üniversitesi