AFFINE FRACTAL LEAST SQUARES REGRESSION MODEL

Cristina Serpa
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Cristina Serpa: Instituto Superior de Engenharia de Lisboa (ISEL), Instituto Politécnico de Lisboa, Lisbon, Portugal2Centro de Matemática, Aplicações Fundamentais e Investigação Operacional (CMAFcIO), Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal

FRACTALS (fractals), 2022, vol. 30, issue 07, 1-19

Abstract: This paper develops a method to find fractal curves to fit real data. With a formulation for fractal functions through a type of affine systems of iterative functional equations, we apply the procedure of minimizing the sum of square residuals that is used in the classical linear regression. We develop formulas for approximation and exact fractal functions for various fractal levels and number of equations. This method gives estimates for the parameters of the equations and corresponding functions, namely the fractal coefficients (vertical scaling factors) and directional coefficients. As a consequence, it is possible to upper estimate the Hausdorff dimension of the fitted curve. We provide worked examples, including estimating a fractal curve for a time series real data set of exchange rates between USD and EUR currencies.

Keywords: Fractal Function; Least Square Regression; Parameter Identification; Fitting Curve; Vertical Scaling Factor (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:30:y:2022:i:07:n:s0218348x22501389

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DOI: 10.1142/S0218348X22501389

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