The Odd Log-Logistic Log-Normal Distribution with Theory and Applications


Ozel G., Altun E., Alizadeh M., Mozafari M.

ADVANCES IN DATA SCIENCE AND ADAPTIVE ANALYSIS, cilt.10, sa.4, 2018 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 10 Sayı: 4
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1142/s2424922x18500092
  • Dergi Adı: ADVANCES IN DATA SCIENCE AND ADAPTIVE ANALYSIS
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI)
  • Anahtar Kelimeler: Log-normal distribution, odd log-logistic distribution, moments, maximum likelihood, PARAMETERS, MOMENTS, FAMILY
  • Hacettepe Üniversitesi Adresli: Evet

Özet

In this paper, a new heavy-tailed distribution is used to model data with a strong right tail, as often occuring in practical situations. The proposed distribution is derived from the log-normal distribution, by using odd log-logistic distribution. Statistical properties of this distribution, including hazard function, moments, quantile function, and asymptotics, are derived. The unknown parameters are estimated by the maximum likelihood estimation procedure. For different parameter settings and sample sizes, a simulation study is performed and the performance of the new distribution is compared to beta log-normal. The new lifetime model can be very useful and its superiority is illustrated by means of two real data sets.