Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/105123
Title: Estimating parameters in autoregressive models in non-normal situations: Symmetric innovations
Authors: Tiku, M.L.
Wong, W.-K.
Bian, G. 
Keywords: Autoregression
Least squares
Maximum likelihood
Modified maximum likelihood
Nonnormality
Robustness
Student's t.
Issue Date: 1999
Citation: Tiku, M.L.,Wong, W.-K.,Bian, G. (1999). Estimating parameters in autoregressive models in non-normal situations: Symmetric innovations. Communications in Statistics - Theory and Methods 28 (2) : 315-341. ScholarBank@NUS Repository.
Abstract: The estimation of coefficients in a simple regression model with autocorrelated errors is considered. The underlying distribution is assumed to be symmetric, one of Student's t family for illustration. Closed form estimators are obtained and shown to be remarkably efficient and robust. Skew distributions will be considered in a future paper. Copyright © 1999 by Marcel Dekker, Inc.
Source Title: Communications in Statistics - Theory and Methods
URI: http://scholarbank.nus.edu.sg/handle/10635/105123
ISSN: 03610926
Appears in Collections:Staff Publications

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