Parameter estimation in a regression model with random coefficient autoregressive errors

DOI10.1016/0378-3758(93)90101-BzbMath0771.62069OpenAlexW1977083923MaRDI QIDQ2368340

Sun Young Hwang, Ishwar V. Basawa

Publication date: 24 August 1993

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(93)90101-b

zbMATH Keywords

nonlinear time seriesregressionlimit distributionleast squares estimators\(m\)-dependent processesrandom coefficient autoregressive errorsweighted central limit theorem

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05)

Related Items

Efficient detection of random coefficients in autoregressive models ⋮ Rate of Convergence to Normality of Estimators in a Random Coefficient ARMA(p,q) Model ⋮ L₁ penalty and shrinkage estimation in partially linear models with random coefficient autoregressive errors ⋮ Shrinkage estimation and variable selection in multiple regression models with random coefficient autoregressive errors ⋮ PARAMETER ESTIMATION IN A PARTLY LINEAR REGRESSION MODEL WITH RANDOM COEFFICIENT AUTOREGRESSIVE ERRORS ⋮ Asymptotic variance–covariance matrix of sample autocorrelations for threshold-asymmetric GARCH processes ⋮ Necessary and sufficient conditions for consistency of \(M\)-estimates in regression models with general errors

Cites Work

• The Stability of Random Coefficient Autoregressive Models
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