Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/62079
Title: Testing serial correlation in partially linear additive errors-in-variables models
Authors: Yang, J
Guo, S
Wei, C
Keywords: Empirical likelihood
Error in variables
Partially linear additive model
Profile least-squares approach
Serial correlation
Issue Date: 2016
Publisher: Taylor & Francis
Source: Communications in statistics. Simulation and computation, 2016, v. 45, no. 9, p. 3114-3127 How to cite?
Journal: Communications in statistics. Simulation and computation 
Abstract: This article considers testing serial correlation in partially linear additive errors-in-variables model. Based on the empirical likelihood based approach, a test statistic was proposed, and it was shown to follow asymptotically a chi-square distribution under the null hypothesis of no serial correlation. Finally, some simulation studies are conducted to illustrate the performance of the proposed method.
URI: http://hdl.handle.net/10397/62079
ISSN: 0361-0918 (print)
1532-4141 (online)
DOI: 10.1080/03610918.2014.920881
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