Kernel density approach to error estimation of MF-DFA measures on time series

DOI10.1016/j.physa.2019.04.099OpenAlexW2939740855WikidataQ128079893 ScholiaQ128079893MaRDI QIDQ2160057

Suemi Rodríguez-Romo, Jesús A. Sosa-Herrera

Publication date: 2 August 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physa.2019.04.099

zbMATH Keywords

time seriesregressionmultifractals

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Uses Software

• LBFGS-B
• BRENT
• Multifractal

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Multifractal detrended fluctuation analysis of nonstationary time series
• Hölder exponent spectra for human gait
• A multifractal description of wind speed records
• Numerical methods for the estimation of multifractal singularity spectra on sampled data: A comparative study
• Use of the Hough transformation to detect lines and curves in pictures
• Fractal measures and their singularities: The characterization of strange sets
• A Limited Memory Algorithm for Bound Constrained Optimization
• Multivariate Density Estimation
• Estimates of the Regression Coefficient Based on Kendall's Tau

This page was built for publication: Kernel density approach to error estimation of MF-DFA measures on time series