SOME APPLICATIONS OF S−LOG-CONVEX FUNCTIONS IN NUMERICAL INTEGRATION

Abstract

Some applications on s-logarithmic convex functions are introduced in this study. s-logarithmic convex functions are used to model risk-averse preferences in economics and finance. They play a role in optimization problems, particularly in nonlinear programming and convex optimization functions. Besides, they are encountered in information theory, machine learning, finance and risk management. These applications highlight importance of s-logarithmic convex functions in various domains, where their mathematical properties are strengthen to model complex phenomena and solve practical problems. s-logarithmic convex functions are particularly useful in numerical integration due to their smooth and well-behaved nature. This study focuses on the role of s-logarithmic functions in determining the upper limit for error in numerical integration. The smoothness and well-behaved derivatives of s-logarithmic convex functions facilitate error analysis in numerical integration.

Keywords

• s−log-convex function
• Perturbed trapezoid inequality
• Numerical integration.

Thanks

The authors would like to thank Prof. Dr. Ali Mutlu for his contributions to the editing of the article.

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