Discriminating between some lifetime distributions in geometric counting processes


PEKALP M. H., Aydogdo H., Turkman K. F.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.51, sa.3, ss.715-737, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 51 Sayı: 3
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1080/03610918.2019.1657452
  • Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Business Source Elite, Business Source Premier, CAB Abstracts, Compendex, Computer & Applied Sciences, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.715-737
  • Anahtar Kelimeler: Geometric counting process, Maximum likelihood estimation, Modified maximum likelihood estimation, Ratio of the maximized likelihood, WEIBULL
  • Ankara Üniversitesi Adresli: Evet

Özet

Gamma, lognormal and Weibull distributions are most commonly used in modeling asymmetric data coming from the areas of life testing and reliability engineering. In this study, we deal with the problem of selecting one of these distributions for a given data set which is consistent with the geometric process (GP) model according to -statistic based on the ratio of the maximized likelihood (RML). First, we show that -statistic performs better than Kolmogorov- Smirnov (KS), mean square error (MSE) and maximum percentage error (MPE) based on extensive simulation study. Then, by using the T-statistic, we determine the distributions of ten real data sets shown to be consistent with the GP model by Lam et al. (2004). After validating the distribution for these data sets, we calculate the estimators of the parameters by using the suitable method given in Lam and Chan (1998), Chan, Lam, and Leung (2004) or Aydogdu, Senoglu, and Kara (2010). Then, we plot observed and the fitted values of the interarrival and arrival times for comparison.