• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.269-279
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• 2002

We considered the problem for confirmation of multiple outliers and leverage points. Identification of multiple outliers and leverage points is difficult because of the masking effect and swamping effect. Rousseeuw and van Zomeren(1990) identified multiple outliers and leverage points by using the Least Median of Squares and Minimum Value of Ellipsoids which are high-breakdown robust estimators. But their methods tend to declare too many observations as extremes. Atkinson(1987) suggested a method for confirming of outliers and Fung(1993) pointed out Atkinson method's limitation and proposed another method by using the add-back model. But we analyzed that Fung's method is affected by adjacent effect. In this thesis, we proposed one procedure for confirmation of outliers and leverage points and compared three example with Fung's method.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.561-571
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• 2007

Local linear regression estimator is the most widely used nonparametric regression estimator which has a number of advantages over the traditional kernel estimators. It is well known that local linear estimator can produce erratic result in sparse regions in the realization of the design and the interpolation method of Hall and Turlach (1997) is the very efficient way to resolve this problem. However, it has been never pointed out that Hall and Turlach's interpolation method is very sensitive to outliers. In this paper, we propose the robust version of the interpolation method for adapting to sparse design. The finite sample properties of the method is compared with Hall and Turlach's method by the simulation study.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.513-515
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• 2022

Manufacturing data collected using IoT devices in a smart factory environment is generally reliable except for noises caused by external factors. However, unlike manufacturing data that is collected mechanically, process data manually recorded by field-workers can cause problems such as the misspelled entries or the missing entries. Therefore, process data must be validated before being used as training data for artificial intelligence models. In this paper, based on the fact that which is a linear relationship between the power consumption of the MCT machine and the production of the product recorded by the field-workers, we detect anomalous records of the workers using robust linear regression.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.650-662
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• 2005

A robust repositioning method is required for annotations to always maintain proper positions when original documents were modified. Robust anchoring in the XML document provides better anchoring results when it includes features of structured documents as well as annotated texts. This paper proposes robust annotation anchoring method in XML document. To do this, this work presents annotation information as logical structure trees, and creates candidate anchors by analyzing matching relations between the annotation and document trees. To select the appropriate candidate anchor among many candidate anchors, this work presents several anchoring criteria based on the textual and label context of anchor nodes in the logical structure trees. As a result, robust anchoring is realized even after various modifications of contexts in the structured document.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.395-406
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• 2022

This paper studies the outlier detection method for multivariate long memory time series. The existing outlier detection methods are based on a short memory VARMA model, so they are not suitable for multivariate long memory time series. It is because higher order of autoregressive model is necessary to account for long memory, however, it can also induce estimation instability as the number of parameter increases. To resolve this issue, we propose outlier detection methods based on the VHAR structure. We also adapt the robust estimation method to estimate VHAR coefficients more efficiently. Our simulation results show that our proposed method performs well in detecting outliers in multivariate long memory time series. Empirical analysis with stock index shows RVHAR model finds additional outliers that existing model does not detect.

• Journal of Korea Water Resources Association
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• v.46 no.9
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• pp.897-907
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• 2013

Climate change is expected to worsen the depletion of streamflow in urban watershed. In this study, we therefore considered the treated wastewater (TWW) use as an adaptation strategy and devised a framework to identify prioritized areas for TWW use. An integrated framework that includes hydrological factors as well as social and environmental components were employed to determine the criteria for decision making. Fuzzy theory was employed to consider the uncertainties in the climate change scenarios and the weights of the performance value. All alternatives were evaluated using the fuzzy TOPSIS method. In addition, statistical method and decision making methods under complete uncertainty were used for robust decision making. As a result, ranking the alternatives using the fuzzy TOPSIS method and robust approach such as maximin, maximax, Hurwicz and equal likelihood criterion mitigated the level of uncertainty and ambiguity in each alternative. The finding of this study can be helpful in prioritizing water resource management projects considering various climate change scenarios.

• Journal of Climate Change Research
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• v.4 no.1
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• pp.11-26
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• 2013

This study examined the applicability of robust decision making (RDM) over standard decision making (SDM) by comparing each result of water supply planning under climate change uncertainties for a Korean dam case. RDM determines the rank of alternatives using the regret criterion which derives less fluctuating alternatives under the risk level regardless of scenarios. RDM and SDM methods were applied to assess hypothetic scenarios of water supply planning for the Andong dam and Imha dam basins. After generating various climate change scenarios and six assumed alternatives, the rank of alternatives was estimated by RDM and SDM respectively. As a result, the average difference in the rank of alternatives between RDM and SDM methods is 0.33~1.33 even though the same scenarios and alternatives were used to be ranked by both of RDM and SDM. This study has significance in terms of an attempt to assess a new approach to decision making for responding to climate change uncertainties in Korea. The effectiveness of RDM under more various conditions should be verified in the future.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.2
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• pp.321-330
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• 2001

Magnetic bearing system is frequently used for high-speed rotating machines because of its frictionless property. But the magnetic bearing system needs feedback controller for stabilization. This paper presents a robust controller design by using linear matrix inequality for magnetic bearing system which shows the control performance and robust stability under the physical parameter perturbations. To the end, the validity of the designed controller is investigated through computer simulation.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.371-381
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• 1993

When the multicollinearity presents in the standard linear regression model, ridge regression might be used to mitigate the effects of collinearity. As the prediction-oriented criterion, the integrated mean sqare error criterion $J_w(k)$ was introduced by Lim, Choi & Park(1980). By noting the equivalent relationship between the $C_k$ criterion and $J_w(k)$ with a special choice of weight function $W(x)$, we propose a more reasonable selection rule of k w.r.t. the $C_k$ criterion than that given in Myers(1986). Next, to find the $\beta(k)$ which behaves reasonably well w.r.t. competing criteria, we adopt the minimax principle in the sense of maximizing the worst relative efficiency of k among competing criteria.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.11a
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• pp.8-9
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• 2011

본 논문에서는 수상 및 수중운동체의 안정성 및 안정화기법에 관해 고찰한다. 선박이 운동을 하게 되면 부가질량이 변하게 되고 대칭인 시스템행렬이 비대칭이 된다. 비대칭성에 따라 시스템의 안정성해석방법도 달라지는데 예를 들어 가속도 피드백을 통해 비대칭요소를 제거하여 대칭으로 변환시키는 것이 가장 대표적인 해석 및 안정화 기법이다. 시스템 모델자체는 어디까지나 모델이기 때문에 대상시스템을 명확하게 수식으로 표현할 수 없으므로 피드백에 의한 비대칭요소를 소거시키는 방법은 타당하지 못하다. 따라서 본 논문에서는 대칭행렬이 비대칭행렬로 변하는 제약에 구애받지 않는, 보다 일반성을 갖는 안정성해석법을 제안한다.