The transmuted odd log-logistic-G family of distributions

Abstract

A new class of models called the transmuted odd log-logistic-G family IS proposed and studied. The method of maximum likelihood is used to estimate the unknown parameters. The performance of the maximum likelihood estimators is assessed in terms of biases and mean squared errors by means of three simulation studies. The usefulness of the proposed family is illustrated by using three real data sets