• 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.

• Journal of the Korean Data and Information Science Society
• /
• 제28권5호
• /
• pp.1191-1204
• /
• 2017

Weighted least squares (WLS) estimation is often easily used for the data with heteroscedastic errors because it is intuitive and computationally inexpensive. However, WLS estimator is less robust to a few outliers and sometimes it may be inefficient. In order to overcome robustness problems, Box-Cox transformation, Huber's M estimation, bisquare estimation, and Yohai's MM estimation have been proposed. Also, more efficient estimations than WLS have been suggested such as Bayesian methods (Cepeda and Achcar, 2009) and semiparametric methods (Kim and Ma, 2012) in heteroscedastic error models. Recently, Çelik (2015) proposed the weight methods applicable to the heteroscedasticity patterns including butterfly-distributed residuals and megaphone-shaped residuals. In this paper, we review heteroscedastic regression estimators related to robust or efficient estimation and describe their properties. Also, we analyze cost data of U.S. Electricity Producers in 1955 using the methods discussed in the paper.

• 로봇학회논문지
• /
• 제7권4호
• /
• pp.231-242
• /
• 2012

This paper proposes particle filter(PF) method using acoustic signal for localization of an underwater robot. The method uses time of arrival(TOA) or time difference of arrival(TDOA) of acoustic signals from beacons whose locations are known. An experiment in towing tank uses TOA information. Simulation uses TDOA information and it reveals dependency of the localization performance on the uncertainty of robot motion and senor data. Also, comparison of the PF method with the least squares method of spherical interpolation(SI) and spherical intersection(SX) is provided. Since PF uses TOA or TDOA which comes from measurement of external information as well as internal motion information, its estimation is more accurate and robust to the sensor and motion uncertainty than the least squares methods.

• 대한간호학회지
• /
• 제29권5호
• /
• pp.1030-1041
• /
• 1999

This study examined those problems noticed under the Asymptotically Generalized Least Squares estimator in evaluating a structural model of physical health. The problems were highly correlated parameter estimates and high standard errors of some parameter estimates. Separate analyses of the endogenous part of the model and of the metric of a latent factor revealed a highly skewed and kurtotic measurement indicator as the focal point of the manifested problems. Since the sample sizes are far below that needed to produce adequate AGLS estimates in the given modeling conditions, the adequacy of the Maximum Likelihood estimator is further examined with the robust statistics and the bootstrap method. These methods demonstrated that the ML methods were unbiased and statistical decisions based upon the ML standard errors remained almost the same. Suggestions are made for future studies adopting structural equation modeling technique in terms of selecting of a reference indicator and adopting those statistics corrected for nonormality.

• 한국음향학회지
• /
• 제40권3호
• /
• pp.213-218
• /
• 2021

입력과 출력에 동시에 잡음이 존재하는 경우 최소 자승법 보다는 완전 최소 자승법이 더 우수한 추정 성능을 보인다는 것이 알려져 있다. 완전 최소 자승법을 시계열 특성을 가지는 데이터에 적용할 경우 보다 실시간 성을 더하기 위해서 Recursive Total Least Squares(RTS) 알고리즘이 제안되어 있다. RTLS는 알고리즘 내에 존재하는 역행렬 계산에서 수치적인 불안정성을 지닌다. 본 논문에서는 RTLS와 유사한 수렴성을 지닐 뿐만 아니라 수치적 불안정성을 줄이기 위한 알고리즘을 제안한다. 이 알고리즘을 위해서 Iterative Wiener Filter(IWF)를 적용한 새로운 RTLS를 제안한다. 시뮬레이션을 통해서 수렴성이 기존의 RTLS와 유사할 뿐만 아니라 수치적 견실성이 기존 RTLS보다 향상되었다는 것을 보인다.

• Communications for Statistical Applications and Methods
• /
• 제11권3호
• /
• pp.485-494
• /
• 2004

An algorithm is proposed to identify multiple outliers in linear regression. It is based on the clustering of residuals from the least median of squares estimation. A cut-height criterion for the hierarchical cluster tree is suggested, which yields the optimal clustering of the regression outliers. Comparisons of the effectiveness of the procedures are performed on the basis of the classic data and artificial data sets, and it is shown that the proposed algorithm is superior to the one that is based on the least squares estimation. In particular, the algorithm deals very well with the masking and swamping effects while the other does not.

• Journal of the Korean Statistical Society
• /
• 제32권4호
• /
• pp.385-399
• /
• 2003

We first introduce the quasi-score estimating function and applied the quasi-score estimating function to nonlinear time series models. We proposed the M quasi-score estimating functions bounded functions for the quasi-score estimating functions. Also, we investigated the asymptotic properties of quasi-likelihood estimators and M quasi-likelihood estimators. Simulation results show that the M quasi-likelihood estimators work better than the least squares estimators under the heavy-tailed distributions

• International Journal of Control, Automation, and Systems
• /
• 제3권3호
• /
• pp.387-396
• /
• 2005

The Rotational/Translational Actuator (RTAC) benchmark problem considers a fourth-order dynamical system involving the nonlinear interaction of a translational oscillator and an eccentric rotational proof mass. This problem has been posed to investigate the utility of a rotational actuator for stabilizing translational motion. In order to experimentally implement any of the model-based controllers proposed in the literature, the values of model parameters are required which are generally difficult to determine rigorously. In this paper, an approach to the least-squares estimation of the parameters of a system is formulated and practically applied to the RTAC system. On the other hand, this paper shows how to model a nonlinear system as a linear uncertain system via nonparametric system identification, in order to provide the information required for linear robust $H_\infty$ control design. This method is also applied to the RTAC system, which demonstrates severe nonlinearities, due to the coupling from the rotational motion to the translational motion. Experimental results confirm that this approach can effectively condense the whole nonlinearities, uncertainties, and disturbances within the system into a favorable perturbation block.

• 전기학회논문지
• /
• 제62권7호
• /
• pp.987-993
• /
• 2013

Integrity of the control and instrumental cables in nuclear power plant is important to maintain the stability of the nuclear power plants. In order to diagnose the integrity of the cables, the diagnostic methods based on reflectometry have been studied. The reflectometry is a non-destructive method and it is applicable to diagnose the live cables. We introduce a Gaussian enveloped linear chirp reflectometry to diagnose the cables in the nuclear power plants. In this paper, we estimate the instantaneous frequency of the Gaussian enveloped linear chirp signal by using the weighted robust least squares filtering to localize the impedance discontinuities in the class 1E instrumental cable.

• 품질경영학회지
• /
• 제46권1호
• /
• pp.39-74
• /
• 2018

Purpose: For more than 30 years, robust parameter design (RPD), which attempts to minimize the process bias (i.e., deviation between the mean and the target) and its variability simultaneously, has received consistent attention from researchers in academia and industry. Based on Taguchi's philosophy, a number of RPD methodologies have been developed to improve the quality of products and processes. The primary purpose of this paper is to review and discuss existing RPD methodologies in terms of the three sequential RPD procedures of experimental design, parameter estimation, and optimization. Methods: This literature study composes three review aspects including experimental design, estimation modeling, and optimization methods. Results: To analyze the benefits and weaknesses of conventional RPD methods and investigate the requirements of future research, we first analyze a variety of experimental formats associated with input control and noise factors, output responses and replication, and estimation approaches. Secondly, existing estimation methods are categorized according to their implementation of least-squares, maximum likelihood estimation, generalized linear models, Bayesian techniques, or the response surface methodology. Thirdly, optimization models for single and multiple responses problems are analyzed within their historical and functional framework. Conclusion: This study identifies the current RPD foundations and unresolved problems, including ample discussion of further directions of study.