A new hybrid conjugate gradient algorithm for optimization models and its application to regression analysis

The hybrid conjugate gradient (CG) method is among the efficient variants of CG for solving optimization problems. This due to their low memory requirements and nice convergence properties. In this paper, we present an unconstrained models show that satisfies sufficient descent condition. global prove proposed would be established under inexact line search. Application famous statistical regression model describing outbreak novel COVID-19 presented. study parameterized using weekly increase/decrease recorded cases from December 30, 2019 March 2020. Preliminary numerical results on some problems promising. Furthermore, produced a good equation confirmed globally.