SiZer analysis for the comparison of time series |
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| Authors: | Cheolwoo Park Amy Vaughan Jan Hannig Kee-Hoon Kang |
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| Institution: | aDepartment of Statistics, University of Georgia, Athens, GA 30602, USA;bDepartment of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA;cDepartment of Statistics, Hankuk University of Foreign Studies, Yongin 449-791, Republic of Korea |
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| Abstract: | SiZer (SIgnificant ZERo crossing of the derivatives) is a scale-space visualization tool for statistical inferences. In this paper we introduce a graphical device, which is based on SiZer, for the test of the equality of the mean of two time series. The estimation of the quantile in a confidence interval is theoretically justified by advanced distribution theory. The extension of the proposed method to the comparison of more than two time series is also done using residual analysis. A broad numerical study is conducted to demonstrate the sample performance of the proposed tool. In addition, asymptotic properties of SiZer for the comparison of two time series are investigated. |
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| Keywords: | Comparison of multiple time series Local linear smoothing Multiple testing adjustment Bandwidth Autocovariance function Weak convergence |
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