• International Journal of Reliability and Applications
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• v.6 no.1
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• pp.1-12
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• 2005

A new test for testing that a life distribution is exponential against the alternative that it is harmonic new better (worse) than used in expectation upper tail HNBUET (HNWUET), but not exponential is presented based on the highly popular 'Kernel methods' of curve fitting. This new procedure is competitive with old one in the sense of Pitman's asymptotic relative efficiency, easy to compute and does not depend on the choice of either the band width or kernel. It also enjoys good power.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.119-127
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• 2004

To test uniformity of a population, we modify the test statistic based on the sample entropy in the literature, and establish its limiting distribution under weaker conditions, which improves the existing results. It is also to study the proposed test statistic based on Vasicek's entropy estimator is consistent.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1077-1094
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• 2011

We accomplish clustering analyses for yeast cell cycle microarray expression data. To reflect the characteristics of a time-course data, we screen the genes using the test statistics with Fourier coefficients applying a FDR procedure. We compare the results done by model-based clustering, K-means, PAM, SOM, hierarchical Ward method and Fuzzy method with the yeast data. As the validity measure for clustering results, connectivity, Dunn index and silhouette values are computed and compared. A biological interpretation with GO analysis is also included.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.427-439
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• 2017

Quade (1967) proposed RANK ANCOVA, which is a nonparametric method to test differences between treatments when there are covariates. Hwang and Kim (2012) also proposed a joint placement test on covariate-adjusted residuals. In this paper, we proposed a new nonparametric method to control the effect of covariate on a response variable that uses linear statistics on covariate adjusted-residuals. The score function used in the linear statistics was proposed by Jeon and Kim (2016). Monte Carlo simulation is also conducted to compare the empirical powers of the proposed method with previous methods.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.101-114
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• 1995

In this paper we consider the multiple unit root tests both for the regular and seasonal unit roots based on the Lagrange Multiplier(LM) principle. Unlike Li(1991)'s method, by plugging the restricted maximum likelihood estimates of the nuisance parameters in the model, we propose a Lagrange multiplier test which does not depend on the existence of the nuisance parameters. The asymptotic distribution of the proposed statistic is derived and empirical percentiles of the test statistic for selected seasonal periods are provided. The power and size of the test statistic for examined for finite samples through a Monte Carlo simularion.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.357-366
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• 1999

Let us assume that two different log-linear models are selected by various model selection methods. When these are non-hierarchical it is not easy to choose one of these models. In this paper the well-known Cox's statistic is applied to compare these non-hierarchical log-linear models. Since it is impossible to obtain the analytic solution about the problem we proposed a alternative method by extending Pesaran and pesaran's (1993) simulation approach. We find that the values of proposed test statistic and the estimates are very much stable with some empirical results.

• Genomics & Informatics
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• v.14 no.4
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• pp.187-195
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• 2016

In genetic association studies with high-dimensional genomic data, multiple group testing procedures are often required in order to identify disease/trait-related genes or genetic regions, where multiple genetic sites or variants are located within the same gene or genetic region. However, statistical testing procedures based on an individual test suffer from multiple testing issues such as the control of family-wise error rate and dependent tests. Moreover, detecting only a few of genes associated with a phenotype outcome among tens of thousands of genes is of main interest in genetic association studies. In this reason regularization procedures, where a phenotype outcome regresses on all genomic markers and then regression coefficients are estimated based on a penalized likelihood, have been considered as a good alternative approach to analysis of high-dimensional genomic data. But, selection performance of regularization procedures has been rarely compared with that of statistical group testing procedures. In this article, we performed extensive simulation studies where commonly used group testing procedures such as principal component analysis, Hotelling's $T^2$ test, and permutation test are compared with group lasso (least absolute selection and shrinkage operator) in terms of true positive selection. Also, we applied all methods considered in simulation studies to identify genes associated with ovarian cancer from over 20,000 genetic sites generated from Illumina Infinium HumanMethylation27K Beadchip. We found a big discrepancy of selected genes between multiple group testing procedures and group lasso.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.1
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• pp.183-191
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• 2013

The purpose of this study is to discover the effects of Reality Therapy group program on leadership life skills, sociality, and classroom unity of elementary school children. The objects of this research are the 34 elementary school children at the K elementary school in the S area of Kyunggi-do, and randomly divided into two groups. Scientific methods are employed to test a Reality Therapy group program as a treatment for elementary school children to increase their level of leadership life skills, sociality, and classroom unity. For this study, one experimental group and one control group, composed of 34 students in total, are organized and treatment is conducted on these groups. The SPSS 12.0 statstics program is employed to analyze the questionnaires of both-test. Mann-Whitney U and Multiple Linear Regression test are used to analyze the result in order to verify the differences between experienced group and controlled group of pre-test scores within the groups. First, the statistics show a difference in leadership life skills factors(p<.001) between the experimental group and the control group. The Reality Therapy group program is a significant predictor of the leadership life skills. These statistics prove that experimental group has higher leadership life skills than the other group. Second, the statistics show a difference in sociality factors(p<.01) between the experimental group and the control group. The Reality Therapy group program is a significant predictor of the sociality. These statistics prove that experimental group have higher positive sociality than the other group. Third, the statistics show a difference in classroom unity factors(p<.001) between the experimental group and the control group. The Reality Therapy group program is a significant predictor of the classroom unity. These statistics prove that experimental group have higher positive classroom unity than the other group.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.115-122
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• 2014

A test for randomness of the binary random sequence is proposed in this paper. The proposed test statistic is based on the mean length of runs distributed with truncated geometric distribution and asymptotically ${\chi}^2_2$-distributed when the size of the sequences is large. A small Monte Carlo simulation compared the size of the test with a significant level as well as evaluated the test power. We applied the proposed method to the sequence of yes or no numbers in Lotto 6/45 and concluded that the randomness of Lotto is retained.

• International Journal of Reliability and Applications
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• v.4 no.4
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• pp.171-181
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• 2003

This paper proposes a U-test statistic for the problem of testing that a life distribution is exponential against the alternative that it is harmonic new better (worse) than used in expectation upper tail HNBUET (HNWUET), but not exponential on complete data. Selected critical values are tabulated for sample sizes n =5(1)60. The asymptotic normality of the statistic is proved and a comparison is made of the asymptotic efficiency between the statistic and other statistics. The power of the test is studied by simulation. A test for HNBUET in the case of randomly right-censored data is also considered. An application of the proposed test statistic in medical sciences is given.