A maximum entropy type test of fit: Composite hypothesis case
AbstractIn this paper, we propose a goodness of fit test based on maximum entropy. As an extension of the result on the simple versus simple hypothesis case handled by Lee et al. (2011), a composite hypothesis case is taken into consideration. To eliminate the parameter estimation effect, we apply the Khmaladze transformation for the empirical process and obtain the asymptotic distribution of the proposed test. The performance of the test is investigated through Monte Carlo simulations.
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 57 (2013)
Issue (Month): 1 ()
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Web page: http://www.elsevier.com/locate/csda
Maximum entropy test; Goodness of fit test; K-transformation; Unstable autoregressive model;
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- repec:cup:cbooks:9780521496032 is not listed on IDEAS
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- Lee, Sangyeol & Vonta, Ilia & Karagrigoriou, Alex, 2011. "A maximum entropy type test of fit," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2635-2643, September.
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