Order of convergence of regression parameter estimates in models with infinite variance

DOI10.1016/0047-259X(89)90049-3zbMath0679.62069OpenAlexW1982381028MaRDI QIDQ1822874

Alain Le Breton, Marek Musiela

Publication date: 1989

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0047-259x(89)90049-3

zbMATH Keywords

heavy tailsinfinite variancestochastic integrationalmost sure convergencestrong consistencymultiple regressionleast squares estimatessemimartingale driven continuous time linear regression model

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Strong limit theorems (60F15)

Related Items (2)

Weighted least squares estimates in linear regression models for processes with uncorrelated increments ⋮ Guaranteed parameter estimation in a first order autoregressive progress with infinite variance

Cites Work

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• Calcul stochastique et problèmes de martingales
• Strong consistency of least squares estimates in multiple regression II
• Convergence of quadratic forms in p-stable random variables and \(\theta _ p\)-radonifying operators
• Strong consistency of least squares estimates in linear regression models driven by semimartingales
• Convergence systems and strong consistency of least squares estimates in regression models
• Random measures and harmonizable sequences

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