Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Regression diagnostics for response transformations in a partial linear model

부분선형모형에서 반응변수변환을 위한 회귀진단

  • Seo, Han Son (Department of Applied Statistics, Konkuk University) ;
  • Yoon, Min (Department of Statistics, Pukyong National University)
  • 서한손 (건국대학교 응용통계학과) ;
  • 윤민 (부경대학교 통계학과)
  • Received : 2012.11.07
  • Accepted : 2012.12.07
  • Published : 2013.01.31
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Abstract

In the transformation of response variable in partial linear models outliers can cause a bad effect on estimating the transformation parameter, just as in the linear models. To solve this problem the processes of estimating transformation parameter and detecting outliers are needed, but have difficulties to be performed due to the arbitrariness of the nonparametric function included in the partial linear model. In this study, through the estimation of nonparametric function and outlier detection methods such as a sequential test and a maximum trimmed likelihood estimation, processes for transforming response variable robust to outliers in partial linear models are suggested. The proposed methods are verified and compared their effectiveness by simulation study and examples.

반응변수의 변환을 고려하는 부분선형모형에서 이상치 문제는 선형모형에서와 마찬가지로 반응변수 변환모수의 추정에 왜곡된 결과를 초래할 수 있다. 이를 해결하기 위해서는 부분선형모형에서 반응변수 변환 모수 추정과 이상치 탐지 과정이 수행되어야 하지만 모형에 포함된 비모수 함수의 비정형성에 따른 어려움이 크다. 본 연구에서는 부분선형모형의 비모수함수에 대한 추정과 순차적 검정, 최대절사우도추정 등과 같은 이상치 제거방법의 적용을 통하여 부분선형모형에서 이상치에 강건한 반응변수 변환 과정을 제안한다. 제안된 방법들은 모의실험과 예제를 통해 효과를 비교 검증한다.

Keywords

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