• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.483-497
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• 2001

When one fits a parametric density function to a data set, it is usually advisable to test the goodness of the postulated model. In this paper we study the nonparametric tests for testing the null hypothesis against general alternatives, when the null hypothesis specifies the density function up to unknown parameters. We modify the test statistic which was proposed by the first author and his colleagues. Asymptotic distribution of the modified statistic is derived and its performance is compared with some other tests through simulation.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.330-335
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• 1995

The rebustness of one sample Chi-square test for multivariate normal mean vector is investigated when the multivariate normal population is mixed with another multivariate normal population with differing in the mean vector. Explicit expressions for the level of significance and power of the test are derived. Some numerical results indicate that the Chi-square test procedure is quite robust against slight mixtures of multivariate normal populations differing in location parameters.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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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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• v.6 no.2
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• pp.479-486
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• 1999

In this paper we propose the test statistic for ordered alternatives on multiple ranked set samples. Since the proposed test statistic is Page type its asymptotic properties are easily obtained. From the simulation works we calculate the power of test statistic($P_{RSS}$) under the underlying distributions such as uniform normal double exponential logistic and Cauchy distribution.

• The Journal of the Korean dental association
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• v.52 no.9
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• pp.558-569
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• 2014

Sample size determination is critical, but not easy to do. Sample size defined as the number of observations in a sample to be studied should be big enough to have a high likelihood of detecting a true difference between groups. Practical procedure for determining sample size, using $G^*$power and previous dental articles, was shown in this study. Examples involving independent t-test, paired t-test, one-way analysis of variance(ANOVA), and one-way repeated-measures(RM) ANOVA were used. The purpose of this study is to enable researchers with non-statistical backgrounds to use in practice freely available statistical software G*power to determine sample size and power.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.11
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• pp.1053-1060
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• 2013

The purpose of this study is to estimate the packing friction of power-operated valve in nuclear power plants. The roll of packing in valve is preventing leakage through stem. Packing friction is highly depend on gland nut tightness which means higher reliability in sealing is lower operability. For the estimation of friction, we used statistical analysis and experimental analysis. In experimental approach, we have performed packing fY test and applied it to valve field test. In statistical approach, we have used 10 years DB of safety-related valve in nuclear power plant and analyzed packing friction based on confidence interval of sample. The comparison of two results shows that statistical analysis for packing friction are more accurate than fY analysis even though both approach have error compared to measured value but we confirmed that statistical approach is proper way to estimate packing friction.

• Journal of electromagnetic engineering and science
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• v.13 no.3
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• pp.192-194
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• 2013

This paper proposes a validation model using a reverberation chamber for verification of the effectiveness and accuracy of the statistical power balance (PWB) method. The PWB method treats electromagnetic (EM) field distributions in certain environments as a representative value of an "ensemble" average, so a reverberation chamber is utilized as a testing apparatus to experimentally simulate the sets of measurement field "ensemble" inside a complex environment. Measurements are performed with various test conditions for environmental loss using flat absorbers, and front and side doors of the chamber. Comparison between the PWB analysis and the measurement results shows good agreement, indicating the usefulness of this statistical analysis method for stating the electromagnetic field inside the EM zone as a representative value to general structures.

• 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.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.459-468
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• 2002

A class of asymmetric beta-ARCH processes is proposed and connections to traditional ARCH models are explained. Geometric ergodicity of the model is discussed. Conditional least squares as well as maximum likelihood estimators of parameters and their limit results are also presented. A test for symmetry of the model is studied with limiting power of test statistic given.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.325-337
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• 1993

This paper propose two test statistics which enable us to proceed the variable selection in Fisher's linear discriminant function for the case of heterogeneous discrimination with equal training sample size. Simultaneous confidence intervals associated with the test are also given. These are exact and approximate results. The latter is based upon an approximation of a linear sum of Wishart distributions with unequal scale matrices. Using simulated sampling experiments, powers of the two tests have been tabulated, and power comparisons have been made between them.