A new exponential estimators for analysis of COVID‐19 risk

Abstract

AbstractCoronavirus disease 2019 (COVID‐19) is the most crucial issue of all countries worldwide as it poses a threat and risk to people in many aspects such as health and economy. Since each country's development level, economy, and infrastructure differ, countries' struggle against COVID‐19 varies. Therefore, understanding the COVID‐19 risk levels of countries can be crucial in determining possible strategies to take specific measures for those at the highest risk. Also, determining the risk level of countries can be more critical than estimates, such as the number of cases and deaths, as the level of risk alone can be an informative indicator for all such issues. Unlike most studies, this study concentrates on evaluating and estimating the COVID‐19 risk level of countries. This study proposes two families of multivariate exponential estimators using two auxiliary attributes. Theoretically, the mean square error (MSE) equations of all proposed exponential estimators are obtained and compared with existing estimators. Some exceptional cases of the multivariate exponential estimators are regarded and compared with MSE values of proposed multivariate exponential estimators. As a result, the multivariate exponential estimators provide more efficient results than all other estimators. These theoretical findings are supported by a numerical illustration using real dataset.