응용통계연구 (The Korean Journal of Applied Statistics)

  • 제35권5호
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  • Pages.579-591
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  • 2022
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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단변량 및 다변량 함수 데이터에 대한 분산분석의 활용

Application of functional ANOVA and functional MANOVA

  • Kim, Mijeong (Department of Statistics, Ewha Womans University)
  • 투고 : 2022.07.19
  • 심사 : 2022.08.25
  • 발행 : 2022.10.31
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초록

함수 데이터는 다양한 분야에서 수집되고 있으며, 집단 간의 함수 데이터를 비교해야하는 경우가 종종 발생한다. 이럴 경우 점별 분산분석 방법을 이용하여 설명하기에는 무리가 있으며, 통합된 결과를 제시할 필요가 있다. 이에 대한 다양한 연구가 제안되었으며, 최근에 R 패키지 fdANOVA로 구현되었다. 이 논문에서 우선 분산분석 및 다변량 분산분석을 설명하고, 최근에 제안된 다양한 단변량 및 다변량 함수 데이터 분산분석을 설명하고자 한다. 또한 R 패키지 fdANOVA의 사용 방법을 설명하고, 이 패키지를 이용하여 서울과 부산 지역의 주별 기온을 단변량 함수 데이터 분산분석을 통해 비교하고, 손글씨 이미지를 다변량 함수 데이터로 변환하여 다변량 함수 데이터 분산분석을 이용하여 비교하고자 한다.

Functional data is collected in various fields. It is often necessary to test whether there are differences among groups of functional data. In this case, it is not appropriate to explain using the point-wise ANOVA method, and we should present not the point-wise result but the integrated result. Various studies on functional data analysis of variance have been proposed, and recently implemented those methods in the package fdANOVA of R. In this paper, I first explain ANOVA and multivariate ANOVA, then I will introduce various methods of analysis of variance for univariate and multivariate functional data recently proposed. I also describe how to use the R package fdANOVA. This package is used to test equality of weekly temperatures in Seoul and Busan through univariate functional data ANOVA, and to test equality of multivariate functional data corresponding to handwritten images using multivariate function data ANOVA.

키워드

과제정보

이 논문은 연구재단 연구 과제 (NRF-2020R1F1A1A01074157)에 의하여 수행되었음.

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