• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.411-416
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• 1998

A simple nonparametric test of complete or total independence is suggested for continuous multivariate distributions. This procedure first discretizes the original variables based on their order statistics, and then tests the hypothesis of complete independence for the resulting contingency table. Under the hypothesis of independence, the chi-squared test statistic has an asymptotic chi-squared distribution. We present a simulation study to illustrate the accuracy in finite samples of the limiting distribution of the test statistic. We compare our method to another nonparametric test of complete independence via a simulation study. Finally, we apply our method to the residuals from a real data set.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.567-574
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• 2003

The estimation problem of predictive value of a positive test(PVP), which is assessing the accuracy of a screening test is considered. Score methods discussed by Gart and Nam(1988) are proposed for constructing confidence interval for PVP. The simulation studies are conducted in evaluating the proposed methods and existing approximate ones.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.947-957
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• 2008

In this paper, we consider the c-sample location problem for ordered alternatives using median ranked ordering-set samples(MROSS). We propose the test statistic using the median of samples that have the same ranked order in each cycle of ranted ordering-set sample(ROSS). We obtain the asymptotic property of the proposed test statistic and Pitman efficiency with respect to other test statistic. In simulation study, our proposed test statistic has good powers for some underlying distributions we consider.

• Journal of the Korean Statistical Society
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• v.13 no.1
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• pp.32-41
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• 1984

An adaptive distribution-free test is proposed for testing the equality of k independent distributions against unrestricted alternatives. In this paper, several rank-sum test statistics are considered as teh components of the adaptive one. The emprical powers of the adaptive testing procedure are compared to those of the classical F test and the component tests through a Monte Carlo study. The results show that the adaptive test has good power properties over a wide class of underlying distributions.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.129-139
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• 2004

We consider the problem of testing for outliers in generalized linear model. We proceed by first specifying a mean shift outlier model, assuming the suspect set of ourliers is known. Given this model, we discuss standard approaches to obtaining score test for outliers as an alternative to the likelihood ratio test.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.587-592
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• 2009

The most frequent use of the chi-square distribution is in the area of goodness-of-t of a distribution. The likelihood ratio test is a commonly used test statistic as the maximum likelihood estimate in statistical inferences. The recently revised versions of the likelihood ratio test statistics are used in estimating the parameter in the chi-square distribution. The estimates are compared with the commonly used method of moments and the maximum likelihood estimate.

• Journal of the Korean Statistical Society
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• v.30 no.3
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• pp.347-366
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• 2001

Robust analogues of the likelihood ratio test are considered for testing of hypotheses involving multiple discrete distributions. The test statistics are generalizations of the Hellinger deviance test of Simpson(1989) and disparity tests of Lindsay(1994), obtained by looking at a 'penalized' version of the distances; harris and Basu (1994) suggest that the penalty be based on reweighting the empty cells. The results show that often the tests based on the ordinary and penalized distances enjoy better robustness properties than the likelihood ratio test. Also, the tests based on the penalized distances are improvements over those based on the ordinary distances in that they are much closer to the likelihood ratio tests at the null and their convergence to the x$^2$ distribution appears to be dramatically faster; extensive simulation results show that the improvement in performance of the tests due to the penalty is often substantial in small samples.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.471-478
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• 2012

In this paper, we present a permutation test to select the number of pairs of canonical variates in canonical correlation analysis. The existing chi-squared test is known to be limited to normality in use. We compare the existing test with the proposed permutation test and study their asymptotic behaviors through numerical studies. In addition, we connect canonical correlation analysis to regression and we we show that certain inferences in regression can be done through canonical correlation analysis. A regression analysis of real data through canonical correlation analysis is illustrated.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.395-406
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• 2001

In this paper, we propose the test statistic for the umbrella alternatives on c-samples ranked set samples(RSS), where the peak of the umbrella is known. We obtain the asymptotic property of the proposed test statistic and the asymptotic relative efficiencies of the proposed test statistic with respect to U-statistic based on simple random samples(SRS). From the simulation work, we compare the empirical powers of the proposed test statistic with U-statistic based on SRS.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.883-890
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• 2010

Since Fisher's exact test is conducted conditional on the observed value of the margin, there are two kinds of the exact power, the conditional and the unconditional exact power. The conditional exact power is computed at a given value of the margin whereas the unconditional exact power is calculated by incorporating the uncertainty of the margin. Although the sample size is determined based on the unconditional exact power, the actual power which Fisher's exact test has is the conditional power after the experiment is finished. This paper investigates differences between the conditional and unconditional exact power Fisher's exact test. We conclude that such discrepancy is a disadvantage of Fisher's exact test.