• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.441-447
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• 2004

Li and Mak (1994) developed a test statistic for detecting the non-linearity and the heteroscedasticity of the time series data. But it is well known that the test statistic may be very sensitive in case of heavy-tailed distributions of the errors. Jiang et al.(2001) suggested the robust method for ARCH models but the calculation procedures for the estimation are very complicated. We suggested the robust method based on Huber's function and our method works quite well rater than the Li and Mak(1994). Also our method is relatively easy to calculate the test statistic.

• Communications for Statistical Applications and Methods
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• 제11권2호
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• pp.247-254
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• 2004

Tusher, Tibshirani and Chu (2001) suggested SAM (Significance Analysis of Microarrays) to compare two groups under different conditions for each gene, using microarray data. They used two sample t-statistic adding fudge factor in the denominator to prevent the value of statistic from being inflated by large sample variance, which might result in significant difference despite of a small value in the numerator. This paper aims at finding robust fudge factor and replacing it in two-sample t-statistic used in SAM, which we call Modified SAM (MSAM). Using the simulated data and data used in Dudoit et al.(2002), it is shown that MSAM find significant genes better and has less error rate than SAM.

• 산업경영시스템학회지
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• 제35권3호
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• pp.52-61
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• 2012

The design method for cumulative sum (CUSUM) control charts, which can be robust to autoregressive moving average (ARMA) modeling errors, has not been frequently proposed so far. This is because the CUSUM statistic involves a maximum function, which is intractable in mathematical derivations, and thus any modification on the statistic can not be favorably made. We propose residual-based robust CUSUM control charts for monitoring autocorrelated processes. In order to incorporate the effects of ARMA modeling errors into the design method, we modify parameters (reference value and decision interval) of CUSUM control charts using the approximate expected variance of residuals generated in model uncertainty, rather than directly modify the form of the CUSUM statistic. The expected variance of residuals is derived using a second-order Taylor approximation and the general form is represented using the order of ARMA models with the sample size for ARMA modeling. Based on the Monte carlo simulation, we demonstrate that the proposed method can be effectively used for statistical process control (SPC) charts, which are robust to ARMA modeling errors.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 춘계 학술발표회 논문집
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• pp.287-293
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• 2003

In this paper we consider the problem of parameter change based on the cusum test proposed by Lee et al. (2003). The cusum test statistic is constructed utilizing the estimator minimizing density-based divergence measures. It is shown that under regularity conditions, the test statistic has the limiting distribution of the sup of standard Brownian bridge. Simulation results demonstrate that the cusum test is robust when there arc outliers.

• 한국인터넷방송통신학회논문지
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• 제11권3호
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• pp.23-30
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• 2011

무선 센서 네트워크에서, 각 센서 노드들로부터 수집된 정보를 효율적으로 활용하기 위해 센서 노드의 정확한 위치 정보는 필수적이다. 센서 노드의 위치를 추정하는 다양한 기법들 중, 일반적으로 많이 사용되는 수신신호세기(RSS)기법은 추가적인 하드웨어 자원 없이 쉽게 구현될 수 있으나 채널 환경에 따라 다양한 표본 데이터들이 수집 될 수 있고, 특히 이상점(outlier)이 포함 될 수 있다. 이러한 이상점들은, 수집된 표본들로부터 통계적 분석(statistical analysis)에 상당한 요인을 미치며 위치 추정 오차를 발생시키는 주요한 원인이 된다. 따라서 본 논문에서는, 이상점이 포함 된 표본들로부터 정확한 위치 추정을 위해 Robust Statistics를 적용한 가우시안 필터 알고리즘을 제안한다. 제안한 알고리즘은 이상점이 포함된 표본들로부터 이상점을 제거하고, 낮은 확률값의 표본들을 배제함으로써 위치 추정의 정확도를 향상시킨다. 시뮬레이션 결과로부터, 이상점이 포함 된 표본들로부터 비 가우시안적 환경에서 제안된 방법의 위치 추정의 정확성 향상과 강인성을 확인하였다.

• Journal of the Korean Statistical Society
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• 제25권3호
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• pp.419-432
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• 1996

When interactions are not present in a three-way layout, the lim-iting null distribution of the F statistic for testing main effects when applied to the rank-score transformed data is the same as the limiting null distribution of the usual F statistic when applied to the normal data. The simulation results exhibit that the rank transform test is robust with respect to significance level and powerful for testing main effects in a three-way factorial experiment.

• Communications for Statistical Applications and Methods
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• 제25권5호
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• pp.559-568
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• 2018

Gene classification can involve complex order-restricted inference. Examining gene expression pattern across groups with order-restriction makes standard statistical inference ineffective and thus, requires different methods. For this problem, Roy's union-intersection principle has some merit. The M-estimator adjusting for outlier arrays in a microarray study produces a robust test statistic with distribution-insensitive clustering of genes. The M-estimator in conjunction with a union-intersection principle provides a nonstandard robust procedure. By exact permutation distribution theory, a conditionally distribution-free test based on the proposed test statistic generates corresponding p-values in a small sample size setup. We apply a false discovery rate (FDR) as a multiple testing procedure to p-values in simulated data and real microarray data. FDR procedure for proposed test statistics controls the FDR at all levels of ${\alpha}$ and ${\pi}_0$ (the proportion of true null); however, the FDR procedure for test statistics based upon normal theory (ANOVA) fails to control FDR.

• 한국콘텐츠학회논문지
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• 제12권5호
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• pp.1-9
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• 2012

디지털 음악과 스마트 폰이 대중화되면서 잡음에 강인한 실시간 음악 핑거프린트 시스템이 다양하게 개발되고 있다. 특히 핑거프린트 알고리즘 중 Multiple Hashing(MLH)은 잡음에 강인하고 정교한 구조로 되어 있다. 본 논문에서는 음악 데이터베이스로부터 질의 및 응답의 정확도를 개선하기 위해 에너지 집중필터를 사용하고 연속성과 중복성을 제거하는 통계적 필터를 제안한다. 에너지 집중 필터는 하위 비트에 에너지가 집중되는 Discrite Cosine Transform(DCT)의 특징을 이용하고, 통계적 필터는 검색된 핑거프린트 정보들 사이의 상관관계 특성을 이용한다. 실험 결과로 잡음 환경에서 에너지와 통계적 필터링으로 구성된 제안 알고리즘은 우수성을 보인다. 이는 제안된 필터 엔진으로 Philips Robust Hash(PRH)보다 잡음에 강인하고 Multiple Hashing(MLH)보다 간결한 핑거프린트 시스템을 구성할 수 있다.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.495-505
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• 2006

A class of robust control for flexible joint manipulators with nonlinearity mismatched uncertainty is designed based on Lyapunov approach. The uncertainties are unknown but their values are within certain prescribed sets. No statistic information of the uncertainties is imposed. The control which utilizes state transformation via virtual control is proposed. The resulting robust control guarantees practical stability for the transformed system and later the stability for the original system is proved. The designed robust control is implemented by experiments in a 2-link flexible joint manipulator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.434-436
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• 1992

In this paper, we propose a new multilevel nonlinear filter for simultaneous edge detection and noise suppression, which we call a order statistic-median hybrid(OMH) filler. The median-related filters cause an edge shift in the presence of an impulse near the edge. The proposed filter reduces such edge shifting while suppressing impulsive as well as nonimpulsive noise. We show that at the noisy edge point the OMH filter is substantially superior to the median filter, the $\alpha$-TM filter and the STM filter[I] in two respects: (a) the output bias error and (b) the output mean square error. Test results confirm that the OMH filter is robust in preserving sharp edges, inhibiting edge shifting, and suppressing a wide variety of noise. The structure for the OMH filter integrated circuit is also described.