• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.467-474
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• 2006

In this paper we present a weighted support vector machine(SVM) and a weighted least squares support vector machine(LS-SVM) for the prediction in the heteroscedastic regression model. By adding weights to standard SVM and LS-SVM the better fitting ability can be achieved when errors are heteroscedastic. In the numerical studies, we illustrate the prediction performance of the proposed procedure by comparing with the procedure which combines standard SVM and LS-SVM and wild bootstrap for the prediction.

• Communications for Statistical Applications and Methods
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• 제18권6호
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• pp.733-739
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• 2011

The linear absolute shrinkage and selection operator(Lasso) method improves the low prediction accuracy and poor interpretation of the ordinary least squares(OLS) estimate through the use of $L_1$ regularization on the regression coefficients. However, the Lasso is not robust to outliers, because the Lasso method minimizes the sum of squared residual errors. Even though the least absolute deviation(LAD) estimator is an alternative to the OLS estimate, it is sensitive to leverage points. We propose a robust Lasso estimator that is not sensitive to outliers, heavy-tailed errors or leverage points.

• 응용통계연구
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• 제21권1호
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• pp.1-17
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• 2008

형제 쌍(sibpair)의 연속형 형질(continuous traits) 자료를 이용한 유전연관성 검정 법(linkage test)으로서 Haseman과 Elston (1972)의 최소제곱(ordinary least square, OLS) 회귀분석법이 주로 사용된다. 비모수적 방법으로서 제시된 Kruglyak과 Lander (1995)의 검정통계량은 Haseman과 Elston (1972)의 방법에 대응되는 방법처럼 보이지만 실제로는 매우 다르다. 본 논문에서는 Kruglyak와 Lander (1995)의 검정통계량과 Haseman과 Elston (1972)의 검정통계량의 관계를 설명하고 모의실험으로 두 검정통계량의 검정력을 비교한다. 유전연관성에 사용되는 형제 자료의 특징은 한정된 설명변수의 값에 매우 많은 자료가 반복(replicated)되었다는 점이며, 이러한 반복 자료에 더욱 적절한 가중 회귀분석법을 제안한다. 가중 회귀분석법의 효율성을 정규분포 또는 정규분포가 아닌 연속형 형질 모의실험 자료로 알아본 결과 형제 쌍 자료의 유전연관성 검정에서 가중 회귀분석법이 다른 검정법들보다도 검정력이 높음을 확인하였다.

• Communications for Statistical Applications and Methods
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• 제9권3호
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• pp.639-647
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• 2002

Efforts to obtain more power for unit root tests have continued. Pantula at el.(1994) compared empirical powers of several unit root test statistics and addressed that the weighted symmetric estimator(WSE) and the unconditional maximum likelihood estimator(UMLE) are the best among them. One can easily see that the powers of these two statistics are almost the same. In this paper we explain a connection between WSE and UMLE and suggest a unit root test statistic which may explain the connection between them.

• Communications for Statistical Applications and Methods
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• 제13권3호
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• pp.765-776
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• 2006

In this paper we propose an estimation method on the regression model with randomly censored observations of the training data set. The weighted least squares support vector machine regression is applied for the regression function estimation by incorporating the weights assessed upon each observation in the optimization problem. Numerical examples are given to show the performance of the proposed estimation method.

• International Journal of Aeronautical and Space Sciences
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• 제16권2호
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• pp.278-294
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• 2015

Considering the guidance and control problem of the near space interceptor (NSI) during the terminal course, this paper proposes a three-channel independent integrated guidance and control (IGC) scheme based on the backstepping sliding mode and finite time disturbance observer (FTDO). Initially, the three-channel independent IGC model is constructed based on the interceptor-target relative motion and nonlinear dynamic model of the interceptor, in which the channel coupling term and external disturbance are regarded as the total disturbances of the corresponding channel. Then, the FTDO is introduced to estimate the target acceleration and control system loop disturbances, and the feed-forward compensation term based on the estimated values is employed to effectively remove the effect of disturbances in finite time. Subsequently, the IGC algorithm based on the backstepping sliding mode is also given to obtain the virtual control moment. Furthermore, a robust least-squares weighted control allocation (RLSWCA) algorithm is employed to distribute the previous virtual control moment among the corresponding aerodynamic fins and reaction jets, which also takes into account the uncertainty in the control effectiveness matrix. Finally, simulation results show that the proposed IGC method can obtain the small miss distance and smooth interceptor trajectories.

• 응용통계연구
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• 제28권4호
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• pp.703-719
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• 2015

본 논문은 평균회귀 2요인 사망률 모형에 코호트 효과를 반영한 개선된 확률론적 사망률 모형을 제시한다. 한국 남자의 사망률 자료를 바탕으로 가중평균최소제곱법과 메트로폴리스 알고리듬을 이용하여 사망률 모형을 추정한 결과 코호트 효과를 반영하는 것이 모형 적합도를 향상시킴을 발견하였다. 국민연금공단과 같은 연금사업자가 자신의 장수위험을 금융시장에 순차적으로 전가하는 수단으로서 옵션방식 이자지급 장수채권의 활용을 제안하고 발행채권의 가격 산출방법을 제시하는 것이 본 논문이 기여하는 점이다. 특히 생존지수에 의해 이자지급 현금흐름이 결정되는 장수채권 가격산출을 위하여 코호트 효과가 매우 중요한 요소임을 강조하였다.

• 전기학회논문지
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• 제62권7호
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• pp.987-993
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• 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.

• 전기학회논문지
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• 제58권12호
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• pp.2520-2528
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• 2009

In this paper, we proposed tracking detection methodology using information granulation-based fuzzy radial basis function neural networks (IG-FRBFNN). According to IEC 60112, tracking device is manufactured and utilized for experiment. We consider 12 features that can be used to decide whether tracking phenomenon happened or not. These features are considered by signal processing methods such as filtering, Fast Fourier Transform(FFT) and Wavelet. Such some effective features are used as the inputs of the IG-FRBFNN, the tracking phenomenon is confirmed by using the IG-FRBFNN. The learning of the premise and the consequent part of rules in the IG-FRBFNN is carried out by Fuzzy C-Means (FCM) clustering algorithm and weighted least squares method (WLSE), respectively. Also, Hierarchical Fair Competition-based Parallel Genetic Algorithm (HFC-PGA) is exploited to optimize the IG-FRBFNN. Effective features to be selected and the number of fuzzy rules, the order of polynomial of fuzzy rules, the fuzzification coefficient used in FCM are optimized by the HFC-PGA. Tracking inference engine is implemented by using the LabVIEW and loaded into embedded system. We show the superb performance and feasibility of the tracking detection system through some experiments.

• Computers and Concrete
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• 제18권6호
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• pp.1065-1082
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• 2016

The main aim of this study is to predict the compressive and flexural strengths of self-compacting mortar (SCM) containing $nano-SiO_2$, $nano-Fe_2O_3$ and nano-CuO using wavelet-based weighted least squares-support vector machines (WLS-SVM) approach which is called WWLS-SVM. The WWLS-SVM regression model is a relatively new metamodel has been successfully introduced as an excellent machine learning algorithm to engineering problems and has yielded encouraging results. In order to achieve the aim of this study, first, the WLS-SVM and WWLS-SVM models are developed based on a database. In the database, nine variables which consist of cement, sand, NS, NF, NC, superplasticizer dosage, slump flow diameter and V-funnel flow time are considered as the input parameters of the models. The compressive and flexural strengths of SCM are also chosen as the output parameters of the models. Finally, a statistical analysis is performed to demonstrate the generality performance of the models for predicting the compressive and flexural strengths. The numerical results show that both of these metamodels have good performance in the desirable accuracy and applicability. Furthermore, by adopting these predicting metamodels, the considerable cost and time-consuming laboratory tests can be eliminated.