• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1145-1155
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• 2007

In this paper, we consider the permutation tests for the multivariate data under the two-sample problem setting. We review some testing procedures, which are parametric and nonparametric and compare them with the permutation ones. Then we consider to try to apply the permutation tests to the multivariate data having the continuous and discrete components together by choosing some suitable combining function through the partial testing. Finally we discuss more aspects for the permutation tests as concluding remarks.

• Journal of the Korean Statistical Society
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• v.26 no.3
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• pp.319-332
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• 1997

The application of multivariate linear rank statistics to data with item nonresponse is considered. Only a modest extension of the complete data techniques is required when the missing data may be thought of as a random sample, and an appropriate modification of the covariances is derived. A proof of the asymptotic multivariate normality is given. A review of some related results in the literature is presented and applications including longitudinal and repeated measures designs are discussed.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.203-212
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• 2006

A chi-squared test of multivariate normality is suggested which is mainly focused on detecting deviations from elliptical symmetry. This test uses Mahalanobis distances of observations to have some power for deviations from multivariate normality. We derive the limiting distribution of the test statistic by a conditional limit theorem. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under two non-normal distributions.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.957-963
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• 2004

A new agreement measure for multivariate interval data by different sets of raters is proposed. The proposed approach builds on Um's multivariate extension of Cohen's kappa. The proposed measure is compared with corresponding earlier measures based on Berry and Mielke's approach and Janson and Olsson approach, respectively. Application of the proposed measure is exemplified using hypothetical data set.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.373-384
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• 2003

In this paper, we formulate multivariate one-sided alternatives and propose a class of nonparametric tests for possibly right censored data. We obtain the asymptotic tail probability (or p-value) by showing that our proposed test statistics have asymptotically multivariate normal distributions. Also, we illustrate our procedure with an example and compare it with other procedures in terms of empirical powers for the bivariate case. Finally, we discuss some properties of our test.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.411-423
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• 2003

In this paper we develop a method for calculating a probability that a particular generalized variance is the smallest of all the K multivariate normal generalized variances. The method gives a way of comparing K multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approach for the probability is intractable and thus a Bayesian method is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach. Necessary theory involved in the method and computation is provided.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.821-827
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• 2012

In this study, we propose a new nonparametric test procedure for the multivariate data. In order to accommodate the generalized alternatives for the multivariate case, we construct test statistics via-values with some useful combining functions. Then we illustrate our procedure with an example and compare efficiency among the combining functions through a simulation study. Finally we discuss some interesting features related with the new nonparametric test as concluding remarks.

• Proceedings of the Safety Management and Science Conference
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• 2010.04a
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• pp.259-265
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• 2010

The research discusses the implementation of control charts tools of MINITAB which are classified according to the type of data and the existence of subgrouping, weight and multivariate covariance. The paper presents the three integrated models by the use of zone, multivariate $T^2$-GV(Generalized Variance) and ARIMA(Autoregressive Integrated Moving Average).

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.223-232
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• 1999

Multivariate quality control charts with combine-accumulate approach and accumulate-combine apprach for monitoring both means and variances under multivariate normal process are investigated. Numerical performances of the charts show that multivariate EWMA chart with accumulate-combine approach can be recommended for all kinds of shift in means and variances.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.263-271
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• 2004

This article presents a new measure of chance-corrected interobserver agreement among multivariate ratings of many observers. Modifying an approach by Berry and Mielke, a new agreement measure is proposed. The important modificaton is to use the volume of simplex composed of data points as the disagreement masure. The proposed measure accounts agreement for multivariate interval observations among many observers. Hypothetical and real-life data sets are analyzed for illustrative purpose.