A novel extended model with versatile shaped failure rate: Statistical inference with Covid -19 applications

Anum Shafiq; Tabassum Naz Sindhu; Naif Alotaibi

doi:10.1016/j.rinp.2022.105398

A novel extended model with versatile shaped failure rate: Statistical inference with Covid -19 applications

Results Phys. 2022 May:36:105398. doi: 10.1016/j.rinp.2022.105398. Epub 2022 Mar 16.

Authors

Anum Shafiq¹, Tabassum Naz Sindhu², Naif Alotaibi³

Affiliations

¹ School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China.
² Department of Statistics, Quaid-i-Azam University, 45320, Islamabad 44000, Pakistan.
³ Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, 11432, Saudi Arabia.

Abstract

Statistical models perform an essential role in data analysis, and statisticians are constantly looking for novel or pretty recent statistical models to fit data sets across a broad variety of fields. In this study, we used modified Kies generalized transformation and the new power function to suggest an unique statistical model. We present and discuss a linear illustration of the density function. Theoretically, quantile function, characteristic function, stochastic ordering, mean, and moments are just a few of the structure properties we discuss. By defining an ideal statistical distribution for assessing the COVID-19 mortality rate, an attempt is performed to determine the model of COVID-19 spread in different nations like the United Kingdom and Italy. In some countries, the novel distribution have been shown to be more appropriate than existing competing models when fitted to COVID-19.

Keywords: Estimation techniques; Least Square Estimates; Lehmann Type I; MKNPF model; Mean square error; Weighted Least Square Estimates.