A new graphical tool of outliers detection in regression models based on recursive estimation

TL;DR

This paper introduces a novel graphical method for detecting outliers in multiple regression models using recursive parameter estimation, demonstrated through simulations and real data applications.

Contribution

The paper proposes a new outlier detection tool based on recursive estimation, enhancing existing methods with a graphical approach.

Findings

Effective outlier detection demonstrated through simulations.

Successful application to real datasets with outliers.

Improved visualization of outliers in regression analysis.

Abstract

We present in this paper a new tool for outliers detection in the context of multiple regression models. This graphical tool is based on recursive estimation of the parameters. Simulations were carried out to illustrate the performance of this graphical procedure. As a conclusion, this tool is applied to real data containing outliers according to the classical available tools.