Maximum likelihood estimators in regression models with infinite variance innovations

DOI10.1007/s00362-002-0133-8zbMath1180.62124OpenAlexW1988120963MaRDI QIDQ1871690

Svetlozar T. Rachev, Vygantas Paulauskas

Publication date: 4 May 2003

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-002-0133-8

zbMATH Keywords

Lévy processesAutoregressionstable distributionsmaximum likelihood estimators

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10)

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Cites Work

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• Limit theory for the sample covariance and correlation functions of moving averages
• Statistical analysis of cointegration vectors
• \(\alpha\)-stable limit theorems for sums of dependent random vectors
• Cointegrated processes with infinite variance innovations
• Asymptotic inference for \(AR(1)\) processes with (nonnormal) stable errors
• Statistical inference in regression with heavy-tailed integrated variables
• Stable limits for partial sums of dependent random variables
• More on \(p\)-stable convex sets in Banach spaces
• On Asymptotic Distributions of Estimates of Parameters of Stochastic Difference Equations
• The Limiting Distribution of the Serial Correlation Coefficient in the Explosive Case
• Towards a unified asymptotic theory for autoregression
• Econometric modeling in the presence of heavy-tailed innovations: a survey of some recent advances
• Operator-Stable Probability Distributions on Vector Groups
• On the Statistical Treatment of Linear Stochastic Difference Equations