Effect of Regular and Irregular Missing Data on the Correlation Integral Analysis of Real-Time Series(Nonlinear Problems)

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概要

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• Missing data which inevitably occurs in observed time series may lead to an erroneous result based on the correlation integral analysis. Effects of data, missing at regular and irregular times, on the analyzed result are estimated. A model estimation is obtained for the Lorenz time series. The effects of the missing data in economic and astronomical time series are estimated using the correlation integral analysis. A convenient method of choosing a time lag is proposed to minimize the effect of regularly missing data.

• 社団法人電子情報通信学会の論文
• 2005-11-01

著者

• KHAN Md.

  Graduate School of Science and Engineering, Saga University

• Khan Md.

  Graduate School Of Science Osaka Prefecture University

• TANIZUKA Noboru

  College of Integrated Arts and Sciences, Osaka Prefecture University

• Tanizuka Noboru

  College Of Integrated Arts And Sciences Osaka Prefecture University

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