Algorithm for the Best Functional Regression Model

Abstract

Regression analysis is widely used in science, engineering, economics and many other fields for modeling relationships between variables and for predicting future observations. Selecting an appropriate regression model is a crucial step towards reliable results. In this work, we consider some popular regression models and discuss their suitability for different types of data. The alternative model is evaluated and compared to other models using statistical measures through a Python-based approach. The results highlight the importance of model selection and provide a simple framework in order to decide the most appropriate regression model for a given dataset.