Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/105436
Title: Time series models with asymmetric innovations
Authors: Tiku, M.L.
Wong, W.-K.
Bian, G. 
Keywords: Gamma distribution
Generalized logistic
Hypothesis testing
Modified likelihood
Nonnormality
Power function
Robustness
Time series
Issue Date: 1999
Citation: Tiku, M.L.,Wong, W.-K.,Bian, G. (1999). Time series models with asymmetric innovations. Communications in Statistics - Theory and Methods 28 (6) : 1331-1360. ScholarBank@NUS Repository.
Abstract: We consider AR(q) models in time series with asymmetric innovations represented by two families of distributions: (i) gamma with support IR : (0, ∞), and (ii) generalized logistic with support IR : (-∞, ∞). Since the ML (maximum likelihood) estimators are intractable, we derive the MML (modified maximum likelihood) estimators of the parameters and show that they are remarkably efficient besides being easy to compute. We investigate the efficiency properties of the classical LS (least squares) estimators. Their efficiencies relative to the proposed MML estimators are very low. Copyright © 1999 by Marcel Dekker, Inc.
Source Title: Communications in Statistics - Theory and Methods
URI: http://scholarbank.nus.edu.sg/handle/10635/105436
ISSN: 03610926
Appears in Collections:Staff Publications

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