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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국통계학회 CSAM(Communications for Statistical Applications and Methods) CSAM(Communications for Statistical Applications and Methods) 제28권 제2호
- 발행연도
- 2021.3
- 수록면
- 135 - 150 (16page)
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초록· 키워드
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We propose principal differential analysis based classification methods. Computations of squared multiple correlation function (RSQ) and principal differential analysis (PDA) scores are reviewed; in addition, we combine principal differential analysis results with the logistic regression for binary classification. In the numerical study, we compare the principal differential analysis based classification methods with functional principal component analysis based classification. Various scenarios are considered in a simulation study, and principal differential analysis based classification methods classify the functional data well. Gene expression data is considered for real data analysis. We observe that the PDA score based method also performs well.
목차
Abstract
1. Introduction
2. Methodology
3. Simulation study
4. Real data analysis
5. Concluding remarks
References
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UCI(KEPA) : I410-ECN-0101-2023-310-001432369