Open AccessSome Estimation for the Parameters and Hazard Function of Kummer Beta Generalized Normal Distribution
Author(s) -
Manal Mahmoud Rashid,
Entsar Arebe Al-Doori
Publication year - 2021
Publication title -
mağallaẗ al-ʿulūm al-iqtiṣādiyyaẗ wa-al-idāriyyaẗ
Language(s) - English
Resource type - Journals
eISSN - 2518-5764
pISSN - 2227-703X
DOI - 10.33095/jeas.v27i127.2144
Subject(s) - mathematics , beta distribution , statistics , maximum likelihood , hazard , distribution (mathematics) , function (biology) , beta (programming language) , normal distribution , least squares function approximation , distribution function , generalized normal distribution , mathematical analysis , computer science , programming language , chemistry , physics , organic chemistry , quantum mechanics , evolutionary biology , estimator , biology
Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the practical side showed that the hazard function is increasing, i.e. the increment in staying the teachers in the service, they will be exposed to a greater failure rate as a result of the staying period which decreases in its turn.