Estimate survival function by using Dagum distribution

Abstract

This paper intends to estimate the unlabeled three parameters for Dagum distribution model depend on censored samples type two; employing the maximum likelihood estimator method to obtain the derivation of the point estimators for all unlabeled parameters depending on iterative techniques, as Newton – Raphson method; then to derive ordinary least squares estimator method. Applying all these methods to estimate related probability functions; death density function, cumulative distribution function, survival function and hazard function (rate function).When examining the numerical results for probability survival function by employing ‘mean squares error measure and mean absolute percentage measure’, this may lead to work on the best method in modeling a set of real data; and this method is “Maximum likelihood estimator method for real censored type II sample”.