The Odd Log-Logistic Generalized Gamma Model: Properties, Applications, Classical And Bayesian Approach

Submit Manuscript | http://medcraveonline.com techniques for building meaningful models. More recently, seve­ ral methods of introducing one or more parameters to generate new distributions have been proposed. Among these methods, the compounding of some discrete and important lifetime distributions has been in the vanguard of lifetime modeling. So, several families of distributions were investigated by compounding some useful lifetime and truncated discrete distributions. The log­logistic (LL) distribution with a shape parameter 0 λ > is a useful model for survival analysis and it is an alternative to the log­normal distribution. Unlike the more commonly used Weibull distribution, the LL distribution has a non­monotonic hazard rate function (hrf), which makes it suitable for modeling cancer survival data. For 1 λ > , the hrf is unimodal and when 1 λ = , the hazard decreases monotonically. The fact that its cumulative distribution function (cdf) has a closed­form is particularly useful for analysis of survival data with censoring.