• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.291-296
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• 2010

In this paper, we consider a versatile test based on percentile tests. The versatile test may be useful when the underlying distributions are unknown or quite different types. We consider two kinds of combining functions for the percentile statistics, the quadratic and summing forms and obtain the limiting distributions under the null hypothesis. Then we illustrate our procedure with an example. Finally we discuss some interesting features of the test as concluding remarks.

• Biomedical Science Letters
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• v.17 no.2
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• pp.151-155
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• 2011

Short tandem repeats (STRs) loci are the genetic markers used for forensic human identity test. With multiplex polymerase chain reaction (PCR) assays, STRs are examined and measured PCR product length relative to sequenced allelic ladders. In the repeat region and the flanking region of the commonly-used STR may have DNA sequence variation. A mismatch due to sequence variation in the DNA template may cause allele drop-out (i.e., a "null" or "silent" allele) when it falls within PCR primer binding sites. The STR markers were co-amplified in a single reaction by using commercial PowerPlex$^{(R)}$ 16 system and AmpFlSTR$^{(R)}$ Identifiler$^{(R)}$ PCR amplification kits. Separation of the PCR products and fluorescence detection were performed by ABI PRISM$^{(R)}$ 3100 Genetic Analyzer with capillary electrophoresis. The GeneMapper$^{TM}$ ID software were used for size calling and analysis of STR profiles. Here, this study described a forensic human identity test in which allelic drop-out occurred in the STR system D18S51. During the course of human identity test, two samples with a homozygous (16, 16 and 21, 21) genotype at D18S51 locus were discovered using the PowerPlex$^{(R)}$ 16 system. The loss of alleles was confirmed when the samples were amplified using AmpFlSTR$^{(R)}$ Identifiler$^{(R)}$ PCR amplification kit and resulted in a heterozygous (16, 20 and 20, 21) genotype at this locus each other. This discrepancy results suggest that appropriate measures should be taken for database comparisons and that allele should be further investigated by sequence analysis and be reported to the forensic community.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.357-363
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• 1998

In this paper we propose a nonparametric lack of fit test based on the bootstrap method for testing the null parametric linear model by using linear smoothers. Most of existing nonparametric test statistics are based on the residuals. Our test is based on the centered bootstrap residuals. Power performance of proposed bootstrap lack of fit test is investigated via Monte carlo simulation.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.195-210
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• 2007

This paper develops a consistent nonparametric test for Granger causality in the context of strong-mixing process, which covers a large class of stationary processes including ARMA and ARCH models. The previously proposed tests require absolute regularity ($\beta$-mixing) more stringent than the strong-mixing condition. We prove the consistency of the test under a high level assumption on the approximation error of U statistic by its projection. Due to the sample splitting, the test statistic we propose is asymptotically normally distributed under the null.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.237-250
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• 2009

We consider a nonparametric test procedure for the multi-sample problem with grouped data. We construct the test statistics based on the scores obtained from the likelihood ratio principle and derive the limiting distribution under the null hypothesis. Also we illustrate our procedure with an example and obtain the asymptotic properties under the Pitman translation alternatives. Also we discuss some concluding remarks. Finally we derive the covariance between components in the Appendix.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.241-246
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• 2013

In this study, we propose a nonparametric simultaneous test procedure for the location translation and scale parameters. We consider the Wilcoxon rank sum test for the location translation parameter and the Mood test for the scale parameter with the quadratic and maximal types of combining functions. Then we derive the limiting null distributions of the combining functions. We illustrate our procedure with an example and compare efficiency by obtaining the empirical powers through a simulation study. Finally, we discuss some interesting features related to the nonparametric simultaneous tests.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.288-295
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• 1995

In this paper a hypotheses test procedure based on the least absolute deviation estimators for the unknown parameters in nonlinear regression models is investigated. The asymptotic distribution of the proposed likelihood ratio test statistic are established voth under the null hypotheses and a sequence of local alternative hypotheses. The asymptotic relative efficiency of the proposed test with classical test based on the least squares estimator is also discussed.

• 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.30 no.1
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• pp.63-76
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• 2001

An adaptive estimation and testing method is proposed for comparing dispersions among several ordered groups. Based upon the large sampling theory for nonparametric quartile estimators, we derive the order restricted estimators and construct a simple test statistic. This test statistic has a mixture of several chi-square distributions as its asymptotic null distribution. The proposed test is illustratively applied to survival time data for the patients with carcinoma of the oropharynx.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.473-481
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• 2001

Shapiro and Wilk (1972) developed a test for exponentiality with origin and scale unknown. The procedure consists of comparing the generalized least squares estimate of scale with the estimate of scale given by the sample variance. However the test statistic is inconsistent. Kim(2001) proposed a modified Shapiro-Wilk's test statistic based on the ratio of tow asymptotically efficient estimates of scale. In this paper, we study the asymptotic behavior of the statistic using the approximation of the quantile process by a sequence of Brownian bridges and represent the limit null distribution as an integral of a Brownian bridge.