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, vol.10, no.4, 2018 (ESCI) identifier

  • Publication Type: Article / Article
  • Volume: 10 Issue: 4
  • Publication Date: 2018
  • Doi Number: 10.1142/s2424922x18500092
  • Journal Name: ADVANCES IN DATA SCIENCE AND ADAPTIVE ANALYSIS
  • Journal Indexes: Emerging Sources Citation Index (ESCI)
  • Keywords: Log-normal distribution, odd log-logistic distribution, moments, maximum likelihood, PARAMETERS, MOMENTS, FAMILY
  • Hacettepe University Affiliated: Yes

Abstract

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.