A Lecturer from the Department of Mathematics Publishes a Scientific Research in the Journal STATISTICS, OPTIMIZATION AND INFORMATION COMPUTING
A Lecturer from the Department of Mathematics Publishes a Scientific Research in the Journal STATISTICS, OPTIMIZATION AND INFORMATION COMPUTING
Publishing a Scientific Research
The lecturer, Asst. Prof. Dr. (Hazem Ghadib Kalat) from the Department of Mathematics at the College of Education for Pure Sciences, published a scientific research entitled (A New Family of Continuous Probability Distributions), in the international Scopus journal (STATISTICS, OPTIMIZATION AND INFORMATION COMPUTING), and within the quarter (Q2). The research aimed to present a new set of optimal probability distributions known as the Survival Power-G (SP-G) family, and uses a specific approach to introduce an additional parameter with the survival function of previous distributions. The use of this family enhances the modeling capabilities of the various existing continuous distributions to find new distributions that are more appropriate for many different data. The research also included applying this approach to the exponential distribution with one parameter, creating a new distribution for the exponential survival power (SP-E) with two parameters. The statistical properties of this new distribution and the maximum likelihood estimator (MLE) are determined, and Monte Carlo simulation is used to explore the efficiency of the two-parameter MLE under varying sample sizes. The study finds that the new distribution is used to analyze three distinct sets of real data. Compared with alternative distributions on these sets of data, the new distribution is shown to outperform the other distributions.
The lecturer, Asst. Prof. Dr. (Hazem Ghadib Kalat) from the Department of Mathematics at the College of Education for Pure Sciences, published a scientific research entitled (A New Family of Continuous Probability Distributions), in the international Scopus journal (STATISTICS, OPTIMIZATION AND INFORMATION COMPUTING), and within the quarter (Q2). The research aimed to present a new set of optimal probability distributions known as the Survival Power-G (SP-G) family, and uses a specific approach to introduce an additional parameter with the survival function of previous distributions. The use of this family enhances the modeling capabilities of the various existing continuous distributions to find new distributions that are more appropriate for many different data. The research also included applying this approach to the exponential distribution with one parameter, creating a new distribution for the exponential survival power (SP-E) with two parameters. The statistical properties of this new distribution and the maximum likelihood estimator (MLE) are determined, and Monte Carlo simulation is used to explore the efficiency of the two-parameter MLE under varying sample sizes. The study finds that the new distribution is used to analyze three distinct sets of real data. Compared with alternative distributions on these sets of data, the new distribution is shown to outperform the other distributions.