Performance of adaptive estimators in slowly varying parameter models

DOI10.1007/s10260-007-0083-3zbMath1405.62116OpenAlexW2016340175MaRDI QIDQ734464

Carlo Grillenzoni

Publication date: 13 October 2009

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-007-0083-3

zbMATH Keywords

mean squared errortime-varying parametersweighted least squaresexponential discountingdynamic models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Cites Work

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• On recursive estimation for time varying autoregressive processes
• Testing for causality in real time
• Fitting time series models to nonstationary processes
• Recursive estimation of a drifted autoregressive parameter.
• Least squares estimator for regression models with some deterministic time varying parameters
• PARSIMONIOUS PERIODIC TIME SERIES MODELING
• Bounded error identification of time-varying parameters by RLS techniques
• BIAS AND COVARIANCE OF THE RECURSIVE LEAST SQUARES ESTIMATOR WITH EXPONENTIAL FORGETTING IN VECTOR AUTOREGRESSIONS
• Performance analysis of general tracking algorithms
• Asymptotic Bias in Parameter Estimation of AR‐Processes Using Recursive Least Squares with Exponential Forgetting

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