• Journal of Integrative Natural Science
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• v.11 no.3
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• pp.154-160
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• 2018

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p-r{\geq}3)$, r = rank(K) with a projection matrix K under the quadratic loss, based on a sample $Y_1$, $Y_2$, ${\cdots}$, $Y_n$. In this paper a James-Stein type estimator with shrinkage form is given when it's variance distribution is specified and when the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is constrain, where K is an idempotent and symmetric matrix and rank(K) = r. It is characterized a minimal complete class of James-Stein type estimators in this case. And the subclass of James-Stein type estimators that dominate the sample mean is derived.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.679-691
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• 2001

Two truncated sequential tests are developed for the two-sample scale problem based on the usual Wilcoxon rank-sum statistic for two different dispersion indices - absolute median deviations, when the medians of the two populations X and Y are equal or known and sums of squared mean deviations, when the medians are either unknown or unequal. The first test is briefly called SWAMD test and the second SWSMD test. For the SWAMD test, the percentile points for both the one-sided and two-sided alternatives, (equation omitted) have been found by Wiener approximation and their values computed for a range of values of a and N; analytical expression for the power function has been derived through Wiener process and its performance studied for various sequential designs for exponential distribution. This test has been illustrated by a numerical example. All the results of the SWAMD test, being directly applicable to the SWSMD test, are not dealt with separately Both the tests are compared and their suitable applications indicated.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.475-486
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• 2015

Mining the microarray data accumulated in the public data repositories can save experimental cost and time and provide valuable biomedical information. Big data analysis pooling multiple data sets increases statistical power, improves the reliability of the results, and reduces the specific bias of the individual study. However, integrating several data sets from different studies is needed to deal with many problems. In this study, I limited the focus to the cross platform classification that the platform of a testing sample is different from the platform of a training set, and suggested a simple classification method based on rank. This method is compared with the diagonal linear discriminant analysis, k nearest neighbor method and support vector machine using the cross platform real example data sets of two cancers.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.115-127
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• 2017

This paper proposes a Bayesian test for the equivalence of survival functions in multiple groups. Proposed Bayesian test use the model of Cox's regression with time-varying coefficients. B-spline expansions are used for the time-varying coefficients, and the proposed test use only the partial likelihood, which provides easier computations. Various simulations of the proposed test and typical tests such as log-rank and Fleming and Harrington tests were conducted. This result shows that the proposed test is consistent as data size increase. Specifically, the power of the proposed test is high despite the existence of crossing hazards. The proposed test is based on a Bayesian approach, which is more flexible when used in multiple tests. The proposed test can therefore perform various tests simultaneously. Real data analysis of Larynx Cancer Data was conducted to assess applicability.

• Journal of Integrative Natural Science
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• v.10 no.1
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• pp.33-39
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• 2017

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p-q{\geq}3)$, $q=rank(P_V)$ with a projection matrix $P_v$ under the quadratic loss, based on a sample $X_1$, $X_2$, ${\cdots}$, $X_n$. We find a James-Stein type decision rule which shrinks towards projection vector when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}{\theta}-P_V{\theta}{\parallel}$ is restricted to a known interval, where $P_V$ is an idempotent and projection matrix and rank $(P_V)=q$. In this case, we characterize a minimal complete class within the class of James-Stein type decision rules. We also characterize the subclass of James-Stein type decision rules that dominate the sample mean.

• Genomics & Informatics
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• v.2 no.4
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• pp.180-183
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• 2004

Comparative Statistic Module(CSM) provides more reliable list of significant genes to genomics researchers by offering the commonly selected genes and a method of choice by calculating the rank of each statistical test based on the average ranking of common genes across the five statistical methods, i.e. t-test, Kruskal-Wallis (Wilcoxon signed rank) test, SAM, two sample multiple test, and Empirical Bayesian test. This statistical analysis module is implemented in Perl, and R languages.

• Korean Journal of Agricultural Science
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• v.29 no.1
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• pp.84-98
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• 2002

Rank of Chungnam's flower industry in Korea is sixth in the number of flower fanning household and fifth in the flower cultivating land size in 2000. However, based on the SWOT analysis of Chungnam's agro-environmental factors influencing flower growing, it is noted that further shift of the regional flower industry up to 2nd highest rank nationally can be demonstrated. Strategies for achieving such targets are suggested as follows ; 1) specializing in flower varieties with regional comparative advantage, such as orchids, lily and rose, 2) establishing the educational system for farmers to manage the risks of market price fluctuation, flower cultivation and agricultural finance properly, 3) enlarging the investments in R&D and research facilities 4) assigning the efficient function and communication among the local government, farmers and agricultural marketeers so as to increase the flower exportation.

• Journal of the Korean Statistical Society
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• v.19 no.2
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• pp.128-138
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• 1990

In this paper we study the properties of nonparametric tests for testing the null hypothesis of no changes against one sided and two sideds alternatives in scale parameter at unknown point. We first propose two types of nonparametric tests based on linear rank statistics and rank-like statistics, respectively. For these statistics, we drive the asymptotic distributions under the null and contiguous alternatives. The main theoreticla tools used for derivation are the stochastic process representation of the test staistic and the Brownian bridge approximation. We evaluate the Pitman efficiencies of the test for the contiguous alternatives, and also compute empirical power by Monte Carlo simulation.

• Journal of Korean Society for Quality Management
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• v.15 no.2
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• pp.50-54
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• 1987

A distribution-free rank test for parallelism of regression lines against ordered alternatives is considered. The proposed test statistic is based on the Kepner-Robinson's transformation. The null distribution of the proposed statistic is the same as that of the Wilcoxon signed rank statistic. But, the proposed procedure can be applied only to four or fewer regression lines. The results of a small-sample Monte Carlo study show that the proposed test is comparable with the parametric test in heavy tailed distributions.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.1009-1014
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• 1994

This paper improves the previously proposed spectral mapping method for supervised speaker adaptation in which a mapped spectrum is interpolated from speaker difference vectors at typical spectra based on a minimized distortion criterion. In estimating these difference vectors, it is important to find an appropriate number of typical points. The previous method empirically adjusts the number of typical points, while the present method optimizes the effective number by rank reduction of normal equation. This algorithm was applied to a supervised speaker adaptation for Korean word recognition using the templates form a prototype male speaker. The result showed that the rank reduction technique not only can automatically determine an optimal number of code vectors, but also slightly improves the recognition scores compared with those obtained by the previous method.