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Multifractal approaches in econometrics and fractal-inspired robust regression

Publication at Faculty of Mathematics and Physics |
2021

Abstract

This paper starts with a discussion of recent data analysis tools inspired by fractal or multifractal concepts. We pay special attention to available data analysis tools based on reciprocal weights assigned to individual observations; these are inspired by an assumed fractal structure of multivariate data.

As an extension, we consider here a novel version of the least weighted squares estimator of parameters for the linear regression model, which exploits reciprocal weights. Finally, we perform a statistical analysis of 31 datasets with economic motivation and compare the performance of the least weighted squares estimator with various weights.