Akademik Veri Yönetim Sistemi
VI. International Applied Statistics Congress, Ankara, Türkiye, 14 - 16 Mayıs 2025, ss.41, (Özet Bildiri)
Since the Weibull distribution is one of the best-known and widely used distributions in various disciplines, such as failure rates, reliability, and survival studies, many studies have been conducted on estimating the parameters of this distribution. Although different estimation methods have been developed for this distribution, the maximum likelihood method is the most widely used and known. Despite this, it is challenging to estimate some distributions' parameters, especially the three-parameter Weibull distribution, by maximizing the likelihood function. Various meta-heuristic methods, such as particle swarm optimization, differential evolution, and genetic algorithms, have been proposed over the years to overcome this difficulty. In this study, the Jaya algorithm, which has not been used for this distribution before, is used, and the algorithm performance is examined for different algorithm parameters, sample sizes, and swarm sizes for different skewness levels of the three-parameter Weibull distribution. A comprehensive Monte-Carlo simulation analysis is performed to examine the performance of the proposed approach, and the performances of different cases are compared in terms of the Deficiency Criterion used to test the efficiency of the methods used in parameter estimation. According to the simulation results, it is observed that the proposed Jaya algorithm gives more efficient results for some cases examined.