Strong convergence of estimators in nonlinear autoregressive models

DOI10.1016/S0047-259X(02)00022-2zbMath1026.62088OpenAlexW2046512769MaRDI QIDQ1873108

Eckhard Liebscher

Publication date: 19 May 2003

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

Full work available at URL: https://doi.org/10.1016/s0047-259x(02)00022-2

zbMATH Keywords

strong convergenceM-estimatorsnonlinear autoregressive modelthreshold models

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (5)

Law of the iterated logarithm for error density estimators in nonlinear autoregressive models ⋮ Maximum likelihood estimators in linear regression models with Ornstein-Uhlenbeck process ⋮ QML estimators in linear regression models with functional coefficient autoregressive processes ⋮ Testing nonstationary and absolutely regular nonlinear time series models ⋮ Strong convergence of estimators as \(\varepsilon_n\)-minimisers of optimisation problems

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