Approximation of the Gompertz function with a multilogistic function

TL;DR

This paper demonstrates that the Gompertz function can be accurately approximated by a sum of three logistic functions using second-order logistic wavelets for parameter estimation.

Contribution

It introduces a novel approximation method for the Gompertz function using a multilogistic function composed of three logistic components.

Findings

High-accuracy approximation of Gompertz by multilogistic functions

Effective parameter estimation with second-order logistic wavelets

Potential applications in modeling growth processes

Abstract

The paper deals with the comparison of the Gompertz function and the logistic function. We show that the Gompertz function can be approximated with high accuracy by a sum of three logistic functions (multilogistic function). Two of them are increasing and one is decreasing. We use second-order logistic wavelets to estimate the parameters of the multilogistic function.