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Independence Test of Time Series Based on Power-Divergence
Emad Ashtari Nezhad , Yadollah Waghei , Gholam Reza Mohtashami Borzadaran , Hamid Reza Nili Sani , Hadi Alizadeh Noughabi
Abstract:   (991 Views)

‎Before analyzing a time series data‎, ‎it is better to verify the dependency of the data‎, ‎because if the data be independent‎, ‎the fitting of the time series model is not efficient‎. ‎In recent years‎, ‎the power divergence statistics used for the goodness of fit test‎. ‎In this paper‎, ‎we introduce an independence test of time series via power divergence which depends on the parameter λ‎. ‎We obtain asymptotic distribution of the test statistic‎. ‎Also using a simulation study‎, ‎we estimate the error type I and test power for some λ and n‎. ‎Our simulation study shows that for extremely large sample sizes‎, ‎the estimated error type I converges to the nominal α‎, ‎for any λ‎. ‎Furthermore‎, ‎the modified chi-square‎, ‎modified likelihood ratio‎, ‎and Freeman-Tukey test have the most power‎.

Keywords: ‎Independence Test‎, ‎Time Series‎, ‎Power-divergence‎, ‎m-dependence Random Variable.
Full-Text [PDF 5010 kb]   (154 Downloads)    
Type of Study: Research | Subject: Time Series
Received: 2017/01/1 | Accepted: 2018/09/5
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مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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