Estimating parameters in autoregressive models in non-normal situations: symmetric innovations

DOI10.1080/03610929908832300zbMath0927.62093OpenAlexW4231660004MaRDI QIDQ4237865

Wing-Keung Wong, Guorui Bian, Moti L. Tiku

Publication date: 14 December 1999

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929908832300

zbMATH Keywords

tablesrobustnessmaximum likelihoodleast squaresmodified maximum likelihoodautoregressionnonnormalityStudent's t family

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (16)

Modified Maximum-Likelihood Method for Non-Normal Time Series Revisited ⋮ ESTIMATING PARAMETERS IN AUTOREGRESSIVE MODELS IN NON-NORMAL SITUATIONS: ASYMMETRIC INNOVATIONS ⋮ Efficient and robust estimation for autoregressive regression models using shape mixtures of skew \(t\) normal distribution ⋮ Estimating parameters of a multiple autoregressive model by the modified maximum likelihood method ⋮ APPLIED REGRESSION ANALYSIS BIBLIOGRAPHY UPDATE 2000–2001 ⋮ Robust parameter estimation of regression model with AR(p) error terms ⋮ Efficient algorithms for robust estimation in autoregressive regression models using Student’stdistribution ⋮ Empirical likelihood estimation for linear regression models with AR(p) error terms with numerical examples ⋮ Linear regression model with new symmetric distributed errors ⋮ Stochastic analysis of covariance when the error distribution is long-tailed symmetric ⋮ Autoregressive processes with normal-Laplace marginals ⋮ Estimating parameters in autoregressive models with asymmetric innovations ⋮ Autoregressive models with mixture of scale mixtures of Gaussian innovations ⋮ Autoregressive models with short-tailed symmetric distributions ⋮ Estimation of autoregressive models with epsilon-skew-normal innovations ⋮ Parameter estimation of regression model with AR\((p)\) error terms based on skew distributions with EM algorithm

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