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Dimension Reduction in Time Series via Partially Quanti ed Principal Componen

부분-수량화를 통한 시계열 자료 분석에서의 차원축소

  • Received : 20100700
  • Accepted : 20100800
  • Published : 2010.10.31

Abstract

We investigate a possible achievement in dimension reduction of time series via partially quantified principal component. Partial quantification technique allows us in modeling to accommodate artificial variable(s) of practical importance which is defined subjectively by the data analyst. Suggested procedures are described and in turn illustrated in detail by analyzing monthly unemployment rates in Korea.

Keywords

Partial quanti cation;seasonal time series;dimension reduction

References

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Acknowledgement

Supported by : 숙명여자대학교