A Time‐Domain Semi‐parametric Estimate for Strongly Dependent Continuous‐Time Stationary Processes

DOI10.1111/j.1467-9892.2003.00329.xzbMath1050.62086OpenAlexW2089769286MaRDI QIDQ4828163

Elias Masry, Takeshi Kato

Publication date: 24 November 2004

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9892.2003.00329.x

zbMATH Keywords

quadratic formscentral limit theoremlong range dependencestationary Gaussian processescovariance functions

Mathematics Subject Classification ID

Central limit and other weak theorems (60F05) Non-Markovian processes: estimation (62M09) Monte Carlo methods (65C05)

Related Items (2)

Semiparametric analysis of long-range dependence in nonlinear regression ⋮ Convergence of integrated superpositions of Ornstein-Uhlenbeck processes to fractional Brownian motion

Cites Work

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• Averaged periodogram estimation of long memory
• Gaussian Semiparametric Estimation of Non-stationary Time Series
• RATE OPTIMAL SEMIPARAMETRIC ESTIMATION OF THE MEMORY PARAMETER OF THE GAUSSIAN TIME SERIES WITH LONG‐RANGE DEPENDENCE

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