• Korean Journal of Optics and Photonics
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• v.17 no.5
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• pp.412-419
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• 2006

We design and fabricate an autostigmatic null lens system assembled in a fixed tube mount in order to evaluate the shape of an aluminum hyperbolic mirror with the diameter of 300 mm and the f-number of 1.98, which is fabricated by a high precision aspherical DTM (diamond turning machine). Also, we evaluate the degree of shape of the aspherical mirror by this autostigmatic null lens testing method. The autostigmatic null lens system assembling in a fixed tube mount has several advantages of light weight, good mechanical stability, etc. The permissible fabricating limits of null lenses and a mount are determined by considering various tolerances to assure the measurement reliability.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.69-76
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• 1996

In a two-way contingency table, the analyst is most interested in the hypotheses of either homogeneity or independence. For testing this as a null hypothesis, Pearson's ${\chi}^2$ statistic is most commonly used in practice. Once the null Hypothesis is rejected, he will further search forcells which caused the rejection of the null hypothesis. For this purpose, so called cell${\chi}^2$ components are used. In this paper, we derive the influence function of an obsevation to the ${\chi}^2$ statistic, with which cells with high influence can be identified.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.1
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• pp.43-50
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• 2019

Statistical hypothesis tests are important for quantifying answers to questions about samples of data. The Step Process of Statistical Hypothesis Testing; state the null hypothesis, State the alternate hypothesis, State the alpha level, Find the z-score associated with alpha level, Find the test statistic using this formula, If the calculated t distribution value from the data is larger than the t distribution value of alpha level, then you are in the Rejection region and you can reject the Null Hypothesis with ($1-{\alpha}$) level of confidence.

• Korean Journal of Optics and Photonics
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• v.15 no.4
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• pp.313-320
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• 2004

We present a null testing method fer aspheric surfaces, utilizing a phase-shifting diffraction grating interferometer along with a binary amplitude computer generated hologram (CGH). The binary amplitude CGH is designed to compensate for the wavefront between a point source and the aspheric surface under test. The fringe visibility of the grating interferometer is controlled easily by selecting suitable grating diffraction orders for the measurement and reference wavefronts or by optimizing the groove shape of the grating used. The binary amplitude CGH is designed by numerical analysis of ray tracing and fabricated using e-beam lithography for autostigmatic testing. Experimental results of a large-scale aspheric mirror surface are discussed to verify the measurement performance of the proposed diffraction grating interferometer.

• Korean Journal of Optics and Photonics
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• v.16 no.1
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• pp.71-78
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• 2005

A null lens system of autostigmatic type, consisting of two mirrors, is designed for testing a large aspherical mirror. The system is theoretically analyzed to determine the limitation of measurement accuracy according to the manufacturing and alignment errors. We confirmed that irregularity of the null lens surface is the principal factor among tolerances in limiting measurement accuracy. Consequently, we can predict that measurement accuracy will be from 5λ/100 to 4λ/1000 according to the amount of this irregularity. That is, we can present the limitation of possible measurement accuracy with actual alignment and manufacturing errors.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.1007-1015
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• 2003

In this paper we introduced a new score generating function for the rank dispersion function in a general linear model. Based on the new score function, we derived the null asymptotic theory of the rank-based hypothesis testing in a linear model. In essence we showed that several rank test statistics, which are primarily focused on our new score generating function and new dispersion function, are mainly distribution free and asymptotically converges to a chi-square distribution.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.645-660
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• 2001

In this paper we propose a goodness-of-fit test statistic for testing the (null) parametric model versus the (alternative) nonparametric model. Most of existing nonparametric test statistics are based on the residuals which are obtained by regressing the data to a parametric model. Our test is based on the bootstrap estimator of the probability that the smoothing parameter estimator is infinite when fitting residuals to cubic smoothing spline. Power performance of this test is investigated and is compared with many other tests. Illustrative examples based on real data sets are given.

• ETRI Journal
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• v.18 no.3
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• pp.207-213
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• 1996

This paper proposes a new nonparametric test for testing the null hypothesis that the MRL is constant against the alternative hypothesis that the MRL is decreasing (increasing) for ramdomly censored data. The proposed test statistic is a L-statistic, and we use L-statistic theory to establish its asymptotic normality of the test statistic. We discuss the efficiency loss due to censoring and also calculate the asymptotic relative efficiencies of our test statistic with respect to the Chen, Hollander and Langberg's test for several alternatives.

• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.189-195
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• 1998

In this paper, we are concerned with the problem of testing the randomness of the coefficients in a first order autoregressive model. A consistent test based on prediction error is suggested. It is shown that under the null hypothesis, the test statistic is asymptotically normal.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.603-613
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• 2001

A test based on score statistic is derived for detecting homoscedasticity of errors in unbalanced random effects linear model. A small simulation study is performed to investigate the finite sample behaviour of the test statistic which is known to have an asymptotic chi-square distribution under the null hypothesis.