|
|
 |
| |
|
|
|
Gompertz Half Logistic Distribution with Applications on Omicron death cases of Nepal and Engineering data |
|
|
|
PP: 1-13 |
|
|
|
doi:10.18576/msl/120101
|
|
|
|
Author(s) |
|
|
|
Laxmi Prasad Sapkota,
Vijay Kumar,
|
|
|
|
Abstract |
|
|
| This article focuses on distribution theory research and introduces a new statistical model to provide the best fit for COVID- 19 and engineering data. The ongoing COVID-19 epidemic has prompted enormous damage worldwide in recent years, making many countries economically unstable. Part of a detailed scientific investigation of this event has not been explored. However, it is critical to have the correct facts and figures in order to take all necessary actions to avoid COVID-19. It is always of interest in the practice and application of probability distribution to provide the best description of the data under consideration. Recent research has demonstrated the new probability model and its utility in modeling data in applied sciences, particularly in engineering and medicine. In this article, we continue our investigation into this topic and suggest a new statistical model. We have developed a new distribution by combining half-logistic distribution and the Gompertz-G family of distribution with three parameters and we named it Gompertz half-logistic distribution. Linear representation of probability density function, reliability function, odd function, hazard function, moments and its generating function, characteristic function, average residual life function, order statistics, and two entropies namely Renyi and q- Entropy of the proposed distribution are discussed. Under the frequentist approach to estimate the parameter, the maximum likelihood, ordinary least square, and Cramer-von Mises estimation methods are used. To inspect the nature of estimation methods, a simulation experiment is conducted. For the application of the suggested model, two real-life data sets one is death cases due to infection of Omicron virus (a new variant of COVID-19) data of Nepal and another is an engineering data set are considered. Seven similar candidate models are fitted to the data sets to select the best model. The results of the comparison support that the suggested model performed better based on goodness-of-fit tests.
|
|
|
|
|
|
|
|
