ABSTRACT
In this paper, we introduce a new class of statistical models to deal with the data sets in the sports and health sectors. The new class is called, a novel exponent power-Y (NovEP-Y) family of distributions. By implementing the NovEP-Y approach, a new model, namely, a novel exponent power-Weibull (NovEP-Weibull) distribution is introduced. Some distributional properties of the NovEP-Y family such as identifiability, order statistics, quantile function, and moments are obtained. The maximum likelihood estimators of the parameters are also derived. Furthermore, a brief Monto Carlo simulation study is conducted to evaluate the performances of the estimators. To show the applicability of the NovEP-Weibull model, two data sets from the sports and health sciences are considered. The first data set represents the time-to-even data collected from different football matches during the period 1964-2018. Whereas, the second data set is taken from the health sector, representing the survival times of the COVID-19 infected patients. Based on some well-known statistical tests, it is observed that the NovEP-Weibull model is a very competitive dis-tribution for modeling the data sets in the sports and health sectors. (c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
ABSTRACT
In this paper, we subedit a search for a randomly moving Coronavirus (COVID-19) among a finite set of different states. We use a monitoring system to search for COVID-19 which is hidden in one of the n cells of the respiratory system in the human body in each fixed number of time intervals m. The expected rescue time of the patient and detecting COVID-19 has been obtained. Also, we extend the results and obtain the total optimal expected search time of COVID-19. The optimal search strategy is derived suing a dynamic programming algorithm. An illustrative real life example introduced to clear the applicability of this model. © 2020 Natural Sciences Publishing. All rights reserved.