• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.565-579
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• 1997

A robust test is proposed for the problem of testing the parallelism of several regression lines against ordered alternatives. The proposed test statistic is based on a linear combination of one-step pairwise GM-estimators. We compare the performance of the proposed test with that of the other tests through a Monte Carlo simulation. The results of the simulation study show that the proposed test has stable levels, good empirical powers in various circumstances, and particularly higher empirical powers under the presence of extreme outliers or leverage points.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.177-182
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• 2012

A structural break in the level as well as in the innovation variance has often been exhibited in economic time series. In this paper we propose robust unit root tests based on a sign-type test statistic when a time series has a shift in its level and the corresponding volatility. The proposed tests are robust to a wide class of partially stationary processes with heavy-tailed errors, and have an exact binomial null distribution. Our tests are not affected by the size or location of the break. We set the structural break under the null and the alternative hypotheses to relieve a possible vagueness in interpreting test results in empirical work. The null hypothesis implies a unit root process with level shifts and the alternative connotes a stationary process with level shifts. The Monte Carlo simulation shows that our tests have stable size than the OLSE based tests.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.337-346
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• 2001

In this paper we consider the problem of identifying and testing the outliers in linear regression. first we consider the problem for testing the null hypothesis of no outliers. The test based on the ratio of two scale estimates is proposed. We show the asymptotic distribution of the test statistic by Monte Carlo simulation and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure based on the suggested test is proposed and shown to perform fairly well. The forward sequential procedure is unaffected by masking and swamping effects because the test statistic is based on robust estimate.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.70-80
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• 1989

A nonparametric test for testing the parallelism of regression lines against ordered alternatives is proposed. The proposed test statistic is based on a linear combination of robust slope estimators. It is a modified version of the Adichie's test statistics based on scores. A snail-sample Monte Carlo study shows that the proposed test is compatible with the Adichie's test.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.166-176
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• 1994

Some rank score tests are proposed for testing the equality of all sampling distribution functions against ordered location-scale alternatives in k-sample problem. Under the null hypothesis and a contiguous sequence of ordered location-scale alternatives, the asymptotic properties of the proposed test statistics are investigated. Also, the asymptotic local powers are compared with each others. The results show that the proposed tests based on the Hettmansperger-Norton type statistic are more powerful than others for the general ordered location-scale alternatives. However, the Shiraishi's tests based on the sum of two Bartholomew's rank analogue statistics are robust.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.231-234
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• 2001

In this paper, we present a robust watermarking technique based on a DCT-domain watermarking approach and an order statistic(OS) filter. The proposed technique inserts one watermark into each of four coefficients within a 2 ${\times}$ 2 block which is scanned on DCT coefficients in the zig-zag ordering from the medium frequency range. The detection algorithm uses an adaptive trimmed mean operator as a local estimator of the embedded watermark to obtain the desired robustness in the presence of additive Gaussian noise and JPEG compression attacks. The performance is analyzed through statistical analysis and numerical experiments. It is shown that the robustness properties against additive noise and JPEG compression attacks are more enhanced than the previous techniques.

• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.77-86
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• 1995

For the problem of testing the parallelism of two regression lines, a robust procedure is proposed and examined. The proposed test statistic is based on the one-step GM-estimators of slope parameters proposed by Song et al. (1994b). These GM-estimators used the Least Trimmed Squares estimates as an initial values so as to obtain high breakdown point. Through a small-sample Monte Carlo simulation the empirical levels and powers of the proposed test are compared with other tests under various error distributions.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.119-131
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• 1995

Based on Monte-Carlo simulation results we propose a robust analysis of variance procedure by utilizing trimmed mean and Winsorized variance. We deal with mainly the one-way classification case. We evaluate the empirical distribution of a pseudo-F statistic based on symmetrically Winsorized sum of squares when the population is normally distributed.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.507-520
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• 1997

In this paper we propose a robust Wald-type test which is based on an efficient Mallows-type one-step GM-estimator. The proposed estimator based on the weight function of Song, Park and Nam (1996) has a bounded influence function and a high breakdown point. Under some regularity conditions, we compute the finite-sample breakdown point, and drive asymptotic normality of the proposed estimator. The level and power breakdown points, influence function and asymptotic distribution of the proposed test statistic are main points of this paper. To compare the performance of the proposed test with other tests, we perform some Monte Carlo simulations.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.471-472
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• 2012

The active shape model(ASM) is one of the most popular methods among the shape prior based segmentation methods based on its strong shape constraints using the statistic of shape information which is acquired from the training set. ASM has a few drawbacks, such as, the lack of shape variability, and the sensitivity for false locally searched points. In this paper, we suggest the patch-wise robust ASM to overcome the limitations of the ASM. In addition to the SSM, we introduce the patch-wise SSM, to reduce the shape inflexibility and to search reliable points with the point reliance measurement. The quantitative and qualitative results show the robustmness and the accuracy of the proposed method.