CENTRAL LIMIT THEOREM FOR THE LOG-REGRESSION WAVELET ESTIMATION OF THE MEMORY PARAMETER IN THE GAUSSIAN SEMI-PARAMETRIC CONTEXT

DOI10.1142/S0218348X07003721zbMath1141.62073OpenAlexW2963882273MaRDI QIDQ3510243

Murad S. Taqqu, Eric Moulines, François Roueff

Publication date: 2 July 2008

Published in: Fractals (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218348x07003721

zbMATH Keywords

long range dependenceARMA processessemi-parametric estimation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Gaussian processes (60G15) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Central limit and other weak theorems (60F05) Inference from stochastic processes and spectral analysis (62M15)

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Cites Work

• Time series: theory and methods
• Gaussian semiparametric estimation of long range dependence
• Estimation of the memory parameter of the infinite-source Poisson process
• On the Spectral Density of the Wavelet Coefficients of Long-Memory Time Series with Application to the Log-Regression Estimation of the Memory Parameter
• AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
• RATE OPTIMAL SEMIPARAMETRIC ESTIMATION OF THE MEMORY PARAMETER OF THE GAUSSIAN TIME SERIES WITH LONG‐RANGE DEPENDENCE
• Wavelet analysis of long-range-dependent traffic
• Statistical study of the wavelet analysis of fractional Brownian motion

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