• 품질경영학회지
• /
• 제27권2호
• /
• pp.112-125
• /
• 1999

In a robust regression model, it is typically assumed that the errors are normally distributed. However, what if the error distribution is deviated from the normality and the response variables are not completely observable due to censoring? For complete data, Kim and Lai(1998) suggested a new adaptive M-estimator with an asymptotically efficient score function. The adaptive M-estimator is based on using B-splines to estimate the score function and simple cross validation to determine the knots of the B-splines, which are a modified version of Kun( 1992). We herein extend this method to right-censored data and study how well the adaptive M-estimator performs for various error distributions and censoring rates. Some impressive simulation results are shown.

• 응용통계연구
• /
• 제6권1호
• /
• pp.79-93
• /
• 1993

회귀모형에 있어서의 Ruppert와 Carroll의 절사 회귀 추정법을 확장하여 회귀 분위수에 의 한 두 개의 두분으로 관측치를 분할하여 각 부분마다 가중치를 달리 부여하는 방법으로 적 합된 L-추정법을 제안하였다. 이 제안된 L-추정법은 특히 비대칭인 오차분포하에서 좋은 효율을 가지고 있었다.

• 한국컴퓨터정보학회논문지
• /
• 제10권2호
• /
• pp.21-30
• /
• 2005

강건 예측 기법은 오류 자료(outliers)를 제거하고 정상 자료(non-outliers)만으로 모델의 파라미터를 구하는 통계적인 방법으로 잘 알려져 있다 기존의 문헌에 소개된 많은 강건 예측 알고리즘들이 있으나 컴퓨터 비전 및 영상 처리 분야에서 가장 많이 사용되는 알고리즘은 M-estimators와 LMS(least-median of squares) 방법이다. 이 중 M-estimators는 어파인 모델(affine model)의 파라미터 측정에 있어 최적의 방법으로 잘 알려져 있다. 그러나 M-estimators는 통계적인 효율성이 높지만 초기화가 적절히 수행되지 않으면 오류 자료를 제거하는 데 문제점을 가진다 따라서 본 논문에서는 이런 문제점을 해결하기 위해 연속적인 시그모이드(sigmoid) 가중치 함수를 사용하여 오류 자료와 정상 자료를 효과적으로 분리하면서 어파인 모델의 파라미터를 효과적으로 측정하는 적응적인 M-estimators 강건 예측 알고리즘을 제안한다. 실험에서는 기존의 강건 예측 방법과 제안된 적응적 강건 예측 방법의 성능을 비교 및 분석하여 제안된 방법의 우수함을 보인다.

• Communications for Statistical Applications and Methods
• /
• 제10권3호
• /
• pp.859-871
• /
• 2003

In this paper we introduce some adaptive M-estimators using selector statistics to estimate the slope of regression model under the symmetric and continuous underlying error distributions. This selector statistics is based on the residuals after the preliminary fit L$_1$ (least absolute estimator) and the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying symmetric distributions in the location model. If we use L$_1$ as a preliminary fit to get residuals, we find the asymptotic distribution of sample quantiles of residual are slightly different from that of sample quantiles in the location model. If we use the functions of sample quantiles of residuals as selector statistics, we find the suitable quantile points of residual based on maximizing the asymptotic distance index to discriminate distributions under consideration. In Monte Carlo study, this adaptive M-estimation method using selector statistics works pretty good in wide range of underlying error distributions.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
• /
• pp.7-12
• /
• 1993

This paper presents a generalized truncated least, squares adaptive algorithm and a two-stage design method. The proposed algorithm is directly derived from the normal equation of the generalized truncated least squares method (GTLSM). The special case of the GTLSM, the truncated least squares (TLS) adaptive algorithm, has a distinct features which includes the case of minimum steps estimator. This algorithm seemed to be best in the deterministic case. For real applications in the presence of disturbances, the GTLS adaptive algorithm is more effective. The two-stage design method proposed here combines the adaptive control system design with a conventional control design method and each can be treated independently. Using this method, the validity of the presented algorithms are examined by the simulation studies of an indirect adaptive control.

• Structural Engineering and Mechanics
• /
• 제75권6호
• /
• pp.685-699
• /
• 2020

Polygonal finite element provides a great flexibility in mesh generation of crack propagation problems where the topology of the domain changes significantly. However, the control of the discretization error in such problems is a main concern. In this paper, a polygonal-FEM is presented in modeling of crack propagation problems via an automatic adaptive mesh refinement procedure. The adaptive mesh refinement is accomplished based on the Zienkiewicz-Zhu error estimator in conjunction with a weighted SPR technique. Adaptive mesh refinement is employed in some steps for reduction of the discretization error and not for tracking the crack. In the steps that no adaptive mesh refinement is required, local modifications are applied on the mesh to prevent poor polygonal element shapes. Finally, several numerical examples are analyzed to demonstrate the efficiency, accuracy and robustness of the proposed computational algorithm in crack propagation problems.

• Communications for Statistical Applications and Methods
• /
• 제3권3호
• /
• pp.113-123
• /
• 1996

Data-dependent (adaptive) choice of asymptotically efficient score functions for rank estimators and M-estimators of regression parameters in a linear regression model with left-truncated and right-censored data are developed herein. The locally adaptive smoothing techniques of Muller and Wang (1990) and Uzunogullari and Wang (1992) provide good estimates of the hazard function h and its derivative h' from left-truncated and right-censored data. However, since we need to estimate h'/h for the asymptotically optimal choice of score functions, the naive estimator, which is just a ratio of estimated h' and h, turns out to have a few drawbacks. An altermative method to overcome these shortcomings and also to speed up the algorithms is developed. In particular, we use a subroutine of the PPR (Projection Pursuit Regression) method coded by Friedman and Stuetzle (1981) to find the nonparametric derivative of log(h) for the problem of estimating h'/h.

• 한국시뮬레이션학회논문지
• /
• 제8권3호
• /
• pp.77-89
• /
• 1999

Simulating rare events, such as probability of cell loss in ATM networks, machine failure in highly reliable systems, requires huge simulation efforts due to the low chance of occurrence. Importance Sampling (IS) has been applied to accelerate the occurrence of rare events. However, it has a drawback of effective biasing scheme to make the estimator of IS unbiased. Adaptive Importance Sampling (AIS) employs an estimated sampling distribution of IS to the system of interest during the course of simulation. We propose Nonparametric Adaptive Importance Sampling (NAIS) technique which is nonparametrical version of AIS. We test NAIS to estimate a probability of rare event in M/M/1 queueing model. Comparing with classical Monte Carlo simulation, the computational efficiency and variance reductions gained via NAIS are substantial. A possible extension of NAIS regarding with random number generation is also discussed.

• 한국음향학회지
• /
• 제29권4호
• /
• pp.229-236
• /
• 2010

위상동기식 변조기법은 주파수 대역폭의 효율과 전송 신뢰도를 높일 수 있으나 수중 채널의 시변 다중경로에 의해 인접 심볼간 간섭이 발생되어 수중통신에 적용하는 데 어려움이 있다. 본 논문에서는 동해 연근해에서 위상동기 변조방식인 BPSK와 QPSK 신호를 전송하고, 시간에 따라 변화하는 다중경로와 위상변동에 의해 왜곡된 수신신호를 보상하기 위한 위상 추정기를 결합한 적응형 등화기를 제안한다. 해상실험을 통해 전송된 위상동기식 변조신호가 수중채널의 시변 다중경로 특성에 의해 왜곡되었음을 보였고 제안된 방법에 의해 왜곡된 신호가 보정됨을 보였다. BPSK와 QPSK 신호 전송시 300 m 거리에서 각각 0.0078, 0.0376의 비트 오류율을 보였으며, 1000 m 거리에서는 0.0146, 0.0293의 비트 오류율을 보였다.

• 한국시뮬레이션학회:학술대회논문집
• /
• 한국시뮬레이션학회 1999년도 춘계학술대회 논문집
• /
• pp.70-79
• /
• 1999

Importance Sampling (IS) has been applied to accelerate the occurrence of rare events. However, it has a drawback of effective biasing scheme to make the estimator from IS unbiased. Adaptive Importance Sampling (AIS) employs an estimated sampling distribution of IS to the systems of interest during the course of simulation. We propose Nonparametric Adaptive Importance Sampling (NAIS) technique which is nonparametrically modified version of AIS and test it to estimate a probability of rare event in M/M/1 queueing model. Comparing with classical Monte Carlo simulation, the computational efficiency and variance reductions gained via NAIS are substantial. A possible extension of NAIS regarding with random number generation is also discussed.