The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Partial least squares regression theory and application in spectroscopic diagnosis of total hemoglobin in whole blood

부분최소제곱회귀(Partial Least Squares Regression) 이론과 분광학적 혈중 헤모글로빈 진단에의 응용

  • 김선우 ((135-230) 서울시 강남구 일원동 50 삼성생명과학연구소 임상의학연구센터) ;
  • 김연주 ((135-230) 서울시 강남구 일원동 50 삼성생명과학연구소 임상의공학연구센터) ;
  • 김종원 ((135-230) 서울시 강남구 일원동 50 삼성서울병원 임상병리과) ;
  • 윤길원 ((135-230) 서울시 강남구 일원동 50 삼성생명과학연구소 임상의공학연구센터)
  • Published : 1997.09.01
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Abstract

PLSR is a powerful multivariate statistical tool that has been successfully applied to the quantitative analyses of data in spectroscopy, chemistry, and industrial process control. Data in spectorscopy is represented by spectrum matrix measured in many wavelengths. Problems of many kinds of noise in data and itercorrelation between wavelengths are quite common in such data. PLSR utilizes whole data set measured in many wavelengths to the analysis, and handles such problems through data compression method. We investigated the PLSR theory, and applied this method to the data for spectroscopic diagnosis of Total Hemoglobin in whole blood.

분광학분야에서 측정되는 자료는 여러 파장에서 측정된 스펙트럼 행렬과 이 스펙트럼을 통하여 알고자하는 어떤 반응치들의 행렬 또는 벡터로 주어진다. 이 경우 측정 자료에의 많은 잡음(noise)과 파장간의 상관관계가 내재한다. 부분최소제곱회귀 방법은 여러 개의 파장에서 측정된 자료를 모두 이용하는데 자료축약과정을 통하여 자료의 잡음 문제와 상관관계 문제를 해결하는 다변량통계방법이다. 본 연구에서는 이러한 자료에 적합한 부분최소제곱회귀의 이론을 알아보고 실제로 측정된 자료를 통하여 주어진 스펙트럼에 대한 반응치의 예측을 부분최소제곱회귀 방법을 이용하여 고찰하였다.

Keywords

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