• 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.

• Journal of the Korean Statistical Society
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• v.33 no.2
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• pp.149-157
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• 2004

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive processes to determine whether or not a time series is stationary. The proposed tests are robust to the outliers and the heteroscedastic errors, and they have an exact binomial null distribution regardless of the period of seasonality and types of median adjustments. A Monte-Carlo simulation shows that the sign test is locally more powerful than the tests based on ordinary least squares estimator (OLSE) for heavy-tailed and/or heteroscedastic error distributions.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.281-286
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• 2003

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive process to determine whether or not a time series is stationary. The tests have an exact binomial null distribution and are robust to the outliers and the heteroscedastic errors. Monte-Carlo simulation shows that the sign test is locally more powerful than the OLSE-based tests for heavy-tailed and/or heteroscedastic error distributions.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.967-976
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• 1999

In this paper we study the Hellinger distance based goodness-of-fit tests that are analogs of likelihood ratio tests. The minimum Hellinger distance estimator (MHDE) in normal models provides an excellent robust alternative to the usual maximum likelihood estimator. Our simulation results show that the Hellinger deviance test (Simpson 1989) based goodness-of-fit test is robust when data contain outliers. The proposed hellinger deviance test(Simpson 1989) is a more direcct method for obtaining robust inferences than an automated outlier screen method used before the likelihood ratio test data analysis.

• Journal of the Korean Statistical Society
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• v.31 no.3
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• pp.301-314
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• 2002

For autoregressive moving average (ARMA) models, robust unit root tests are developed using M-estimators. The tests are parametric in the sense ARMA parameters are estimated jointly with unit roots. A Monte-Carlo experiment reveals superiority of the parametric tests over the semipararmetric tests of Lucas (1995a) in terms of both empirical sizes and powers.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.11-23
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• 2011

Robust unit root tests are developed for dynamic panels consisting of TAR processes. The test statistics are all based on diverse combinations of individual t-type tests for significance of TAR coefficients. Limiting null distributions are established. A Monte-Carlo experiment compares the proposed tests. The tests are applied to a panel data set of Canadian unemployment rates which show asymmetric features as well as having outliers.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.2 s.107
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• pp.207-213
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• 2006

In our previous research, we proposed a robust saturation controller which involves both control input saturation and structured real parameter uncertainties. This controller can analytically prescribed the upper and lower bounds of parameter uncertainties, and guarantee the closed-loop robust stability of the system in the presence of actuator's saturation. And the availability and the effectiveness of the proposed robust saturation controller were verified through numerical simulations. In this paper, we verify the robust stability of this controller through experimental tests. Expecially, we show unstable cases of other controllers in comparison with this controller. Experimental tests are carried out in the laboratory using a two-story test structure with a hydraulic-type active mass damper.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.223-226
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• 2005

In previous research, we proposed robust saturation controller which involves both actuator's saturation and structured real parameter uncertainties. This controller can analytically prescribed the upper and lower bounds of parameter uncertainties, and guarantee the closed-loop robust stability of the system in the presence of actuator's saturation. And the availability and the effectiveness of the proposed robust saturation controller were verified through numerical simulations. In this paper, we verify the robust stability of this controller through experimental tests. Especially, we show unstable cases of other controllers in comparison with this controller. Experimental tests are carried out in the laboratory using a two-story test structure with a hydraulic-type active mass damper.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.399-408
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• 2016

There is a need to detect heteroscedasticity in a regression analysis; however, it invalidates the standard inference procedure. The diagnostics on heteroscedasticity may be distorted when both outliers and heteroscedasticity exist. Available heteroscedasticity detection methods in the presence of outliers usually use robust estimators or separating outliers from the data. Several approaches have been suggested to identify outliers in the heteroscedasticity problem. In this article conventional tests on heteroscedasticity are modified by using a sequential outlier detection methods to separate outliers from contaminated data. The performance of the proposed method is compared with original tests by a Monte Carlo study and examples.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.2 s.48
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• pp.83-90
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• 2006

In active vibration control of building, controller design considering both control input saturation of controller and parameter uncertainties of building is needed. In our previous research, we proposed a robust saturation controller which guarantees robust stability and control performance of the uncertain linear time-invariant system in the presence of control input saturation. In this paper, the availability of the robust saturation controller for the building with an active mass damper (AMD) system is verified through experimental tests. Experimental tests are carried oui using a two-story building model with a hydraulic-type AMD.