Statistical analysis of DWT coefficients of fGn processes using ARFIMA(p,d,q) models

DOI10.1016/j.physa.2020.124404OpenAlexW3009745287MaRDI QIDQ2140429

Vikram M. Gadre, E. Chandrasekhar, Shivam Bhardwaj

Publication date: 20 May 2022

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

Full work available at URL: https://doi.org/10.1016/j.physa.2020.124404

zbMATH Keywords

Bayesian information criteriaAkaike information criteriaARFIMA(p,d,q) models

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Cites Work

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• Estimation of Hurst exponent revisited
• Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series
• Stochastic analysis of the fractional Brownian motion
• Estimating long-range dependence: Finite sample properties and confidence intervals
• Correlation properties of (discrete) fractional Gaussian noise and fractional Brownian motion
• Log-periodogram regression of time series with long range dependence
• Characterization of ionospheric total electron content data using wavelet-based multifractal formalism
• Fitting autoregressive models for prediction
• A Suggested Statistical Model of some Time Series which occur in Nature
• THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
• AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
• Correlation structure of the discrete wavelet coefficients of fractional Brownian motion
• Ten Lectures on Wavelets
• A wavelet-based joint estimator of the parameters of long-range dependence
• Fractal estimation from noisy data via discrete fractional Gaussian noise (DFGN) and the Haar basis
• Stochastic Calculus for Fractional Brownian Motion and Applications
• Fractional Brownian Motions, Fractional Noises and Applications

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