Maximum Likelihood Estimation in Dagum Distribution with Censored Samples

In this work, we show that the Dagum distribution may be a competitive model for describing data which include censored observations in lifetime and reliability problems. Maximum likelihood estimates of the three parameters of the Dagum distribution are determined from samples with type I right and type II doubly censored data. We perform an empirical analysis using published censored datasets: in certain cases, the Dagum distribution fits better than other parametric distributions that are more commonly used in survival and reliability analysis. Graphical comparisons con firm that the Dagum model behaves better than a num- ber of competitive distributions in describing the empirical hazard rate of the analyzed data. A probability plot to provide graphical check of the appropriateness of the Dagum model for right censored data is constructed and the details are given in the Appendix. Finally, a simulation study is carried out that shows the good performance of the maximum likelihood estimators of the Dagum shape parameters for the type II doubly censored samples.