• Journal of the Korean Statistical Society
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• 제27권3호
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• pp.369-383
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• 1998

This paper deals with a robust regression estimator. We propose an efficient one-step GM-estimator, which has a bounded influence function and a high breakdown point. The main idea of this paper is to use the Mallows-type weights which depend on both the predictor variables and the residuals from a high breakdown initial estimator. The proposed weighting scheme severely downweights the bad leverage points and slightly downweights the good leverage points. Under some regularity conditions, we compute the finite-sample breakdown point and prove the asymptotic normality. Some simulation results and a numerical example are also presented.

• Journal of the Korean Statistical Society
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• 제20권2호
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• pp.177-190
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• 1991

In this paper, we discuss and review various measures which have been presented for studying outliers. high-leverage points, and influential observations when principal component regression is adopted. We suggest several diagnostics measures when principal component regression is used. A numerical example is illustrated. Some individual data points may be flagged as outliers, high-leverage point, or influential points.

• Journal of the Korean Statistical Society
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• 제25권4호
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• pp.471-487
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• 1996

In this paper we propose an efficient scoring type one-step GM-estimator, which has a bounded influence function and a high break-down point. The main point of the estimator is in the weighting scheme of the GM-estimator. The weight function we used depends on both leverage points and residuals So we construct an estimator which does not downweight good leverage points Unider some regularity conditions, we compute the finite-sample breakdown point and prove asymptotic normality Some simulation results are also presented.

• Communications for Statistical Applications and Methods
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• 제17권4호
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• pp.541-550
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• 2010

$L_1$-회귀추정량이 수직이상점에 대해서는 매우 로버스트하지만 지렛점에 대해서는 전혀 로버스트하지 않다는 사실은 잘 알려져 있다. 본 논문에서는 수직이상점은 물론 지렛점에 대해서도 로버스트한 $L_1$-회귀추정을 위한 알고리즘을 제안한다. MCD 또는 MVE-추정량에 바탕을 둔 로버스트거리를 기준으로 지렛점들을 식별하고, 식별된 지렛점들의 영향력을 적절히 감소시키기 위한 가중치를 결정한다. 가중치에 의해 변환된 자료에 선형척도변환 기법에 바탕을 둔 선형계획 알고리즘을 적용함으로써 $L_1$-회귀추정량의 붕괴점을 향상시킨다. 다양한 형태와 규모의 자료에 대한 모의실험 결과, 제안된 알고리즘에 의한 $L_1$-회귀추정량의 붕괴점이 크게 향상되는 것으로 나타났다.

• Communications for Statistical Applications and Methods
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• 제1권1호
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• pp.27-32
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• 1994

We propose a robust regression estimator which has both a high breakdown point and a bounded influence function. The main contribution of this article is to present a weight function in the generalized M (GM)-estimator. The weighting schemes which control leverage points only without considering residuals cannot be efficient, since control leverage points only without considering residuals cannot be efficient, since these schemes inevitably downweight some good leverage points. In this paper we propose a weight function which depends both on design points and residuals, so as not to downweight good leverage points. Some motivating illustrations are also given.

• 로봇학회논문지
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• 제16권3호
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• pp.189-198
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• 2021

In this paper, we introduce the software/hardware system that can reliably calculate the distance from sensor to the model regardless of point cloud density. As the 3d point cloud map is widely adopted for SLAM and computer vision, the accuracy of point cloud map is of great importance. However, the 3D point cloud map obtained from Lidar may reveal different point cloud density depending on the choice of sensor, measurement distance and the object shape. Currently, when measuring map accuracy, high reflective bands are used to generate specific points in point cloud map where distances are measured manually. This manual process is time and labor consuming being highly affected by Lidar sparsity level. To overcome these problems, this paper presents a hardware design that leverage high intensity point from three planar surface. Furthermore, by calculating distance from sensor to the device, we verified that the automated method is much faster than the manual procedure and robust to sparsity by testing with RGB-D camera and Lidar. As will be shown, the system performance is not limited to indoor environment by progressing the experiment using Lidar sensor at outdoor environment.

• Journal of applied mathematics & informatics
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• 제4권2호
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• pp.501-512
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• 1997

In multiple linear regression model we have presupposed assumptions (independence normality variance homogeneity and so on) on error term. When case weights are given because of variance heterogeneity we can estimate efficiently regression parameter using weighted least squares estimator. Unfortunately this estimator is sen-sitive to outliers like ordinary least squares estimator. Thus in this paper we proposed some statistics for detection of outliers in weighted least squares regression.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2005년도 공동학술대회 논문집
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• pp.273-280
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• 2005

MT 전달함수의 추정과정에서 로버스트 방법의 적용은 현재 전자탐사 분야에서 일반적이다. 적절하게 고안되고 적용된 로버스트 방법은 출력 채널인 전기장에 포함되어 있는 외치의 영향을 감소시킬 수 있으나, HLP(High leverage point)라 불리 우는 자기장(입력 채널)의 외치에 종종 민감하지 못하다. 이 문제를 해결하기 위해 HLP의 영향을 최소화할 수 있는 BI(Bounded Influence) 추정이 제안되었고, 전통적인 로버스트 방법보다 신뢰성 있는 전달함수를 제공하는 것으로 보고되었다. 이는 BI 추정이 M-추정을 적용함과 동시에 자기장 성분만으로 결정되는 모자행렬의 통계적인 특성을 고려하여 가중치를 부여하는 방법이기 때문이다. 본 연구에서는 전달함수 추정과정에 BI 추정을 적용하고, 이와 더불어 전처리 단계로서 전자기장의 통계적 분포를 이용해 주파수 영역에서 극단적인 전기장과 자기장 자료의 영향을 감소시키는 기법을 개발하였다. 개발된 전처리 기법은 BI 추정으로 제거될 수 없는 자료를 주파수 영역에서 효과적으로 제거하는 것으로 생각된다. 본 연구에서 개발된 기법의 효율성과 장점은 합성 자료와 현장 자료를 이용하여 도시될 것이다.

• Journal of the Korean Statistical Society
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• 제29권3호
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• pp.285-294
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• 2000

In analyzing bivariate date the sample correlation coefficient is often used, and it is quite sensitive to one or few isolated cases. In this article we derive a formula for the effect of $textsc{k}$ observations on the samples correlation coefficient by the deletion method. To give a reference value for the isolated cases the asymptotic distribution fo the formula is derived. Also, we give some interpretations on several types of isolated cases and an example based on a real data set.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 I
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• pp.633-636
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• 2003

An Ethernet passive optical network(EPON) is a point-to-multipoint optical network. EPONs leverage the low cost, high performance curve of Ethernet systems to provide reliable data, voice and video to end user at bandwidths far exceeding current access technologies. In this paper, we propose the economical and flexible structure of optical network unit(ONU) converting optical format traffic to the customer's desired format(Ethernet, VDSL, T1, IP multicast, etc.). A unique feature of EPONs is that in addition to terminating and converting the optical signal the ONU provide Layer 2-3 switching functionality, which allows internal routing of enterprise traffic at the ONU.