Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30044
Title: Testing Normality for Linear AR(p) Models
Authors: Ip, WC
Wong, H 
Chen, M
Keywords: Cramer-Von Mises statistic
Goodness of fit statistic
Study of power
Testing normality
Issue Date: 2004
Publisher: Marcel Dekker Inc
Source: Communications in statistics - theory and methods, 2004, v. 33, no. 4, p. 891-908 How to cite?
Journal: Communications in Statistics - Theory and Methods 
Abstract: This paper proposes a nonparametric mixed test for normality of linear autoregressive time series. The test is based on the best one-step forecast in mean square with time reverse. The test statistic is the mixture of a goodness of fit statistic and Cramer-Von Mises statistic. Some asymptotic properties are developed for the test.Simulated results have shown that the test is easy to use and has good powers. Three examples of applying the test to real data are also included.
URI: http://hdl.handle.net/10397/30044
ISSN: 0361-0926
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