The quasi-likelihood approach to statistical inference on multiple time-series with long-range dependence

DOI10.1016/0304-4076(95)01738-0zbMath0854.62085OpenAlexW1993842860MaRDI QIDQ1922364

Yuzo Hosoya

Publication date: 14 January 1997

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(95)01738-0

zbMATH Keywords

singularitiesspectrumlarge-sample theoryunified approachquasi-likelihood ratio testfractional ARIMAbracketing function approachmultiple long-memory time-seriesquasi-maximum-likelihood estimation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of parametric tests (62F05)

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Cites Work

• The bracketing condition for limit theorems on stationary linear processes
• Correction to: A central limit theorem for stationary processes and the parameter estimation of linear processes
• The decomposition and measurement of the interdependency between second- order stationary processes
• Efficient parameter estimation for self-similar processes
• Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series
• Long memory relationships and the aggregation of dynamic models
• Smoothed periodogram asymptotics and estimation for processes and fields with possible long-range dependence
• Gaussian semiparametric estimation of long range dependence
• A central limit theorem for quadratic forms in strongly dependent linear variables and its application to asymptotical normality of Whittle's estimate
• AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
• LONG-RANGE DEPENDENCE, NON-LINEARITY AND TIME IRREVERSIBILITY
• Vector linear time series models
• Vector Autoregressions and Causality
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