The transmuted odd log-logistic-G family of distributions
Morad Alizadeh, Haitham M. Yousof, Seyed Mahdi Amir Jahanshahi, Seyed Morteza Najibi, G. G. Hamedani
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
Topics & Concepts
EstimatorMathematicsMaximum likelihoodStatisticsClass (philosophy)Logistic regressionComputer scienceArtificial intelligenceStatistical Distribution Estimation and ApplicationsProbabilistic and Robust Engineering DesignStatistical Methods and Bayesian Inference