The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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LAD Estimators for Categorical Data Analysis

범주형 자료 분석을 위한 LAD 추정량

  • 최현집 (경기대학교 경제학부 응용정보통계전공)
  • Published : 2003.03.01
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Abstract

In this article, we propose the weighted LAD (least absolute deviations) estimators for multi-dimensional contingency tables and drive an estimation method to estimate the proposed estimators. To illustrate the robustness of the estimators, simulation results are presented for several models Including log-linear models and models for ordinal variables in multidimensional contingency tables. Examples were also introduced.

일반적인 다차원 분할표 분석을 위해 고려 할 수 있는 로그 선형 모형 (log-linear model)과 순위 변수(ordered variables)가 고려된 여러 연관성 모형(association models)을 위한 가중값이 부여된 LAD(least absolute deviations) 추정량을 제안하고 추정을 위한 반복 추정법을 제안하였다. 모의실험을 통하여 제안된 LAD추정량이 최우추정량에 비해 로버스트한 성질을 갖는 다는 것을 밝히고, 이상칸 식별을 위해 많은 선행 연구들에서 인용된 자료들의 경험적 분석을 통해 제안된 추정량과 추정방법이 가질 수 있는 문제점과 특징에 관하여 토론하였다

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  1. Trimmed LAD Estimators for Multidimensional Contingency Tables vol.23, pp.6, 2010, https://doi.org/10.5351/KJAS.2010.23.6.1235