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http://dx.doi.org/10.5351/KJAS.2010.23.1.073

Nonstationary Time Series and Missing Data  

Shin, Dong-Wan (Department of Statistics, Ewha Woman's University)
Lee, Oe-Sook (Department of Statistics, Ewha Woman's University)
Publication Information
The Korean Journal of Applied Statistics / v.23, no.1, 2010 , pp. 73-79 More about this Journal
Abstract
Missing values for unit root processes are imputed by the most recent observations. Treating the imputed observations as if they are complete ones, semiparametric unit root tests are extended to missing value situations. Also, an invariance principle for the partial sum process of the imputed observations is established under some mild conditions, which shows that the extended tests have the same limiting null distributions as those based on complete observations. The proposed tests are illustrated by analyzing an unequally spaced real data set.
Keywords
High frequency data; invariance principle; missing value imputation; semiparametric unit root test;
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