• Journal of the Korean Statistical Society
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• v.7 no.1
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• pp.17-26
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• 1978

For testing $\beta_i=\beta, i=1,...,k$, in the regression model $Y_{ij} = \alpha_i + \beta_ix_{ij} + e_{ij}, j=1,...,n_i$, a simple and robust test based on Kendall's tau is proposed. Its asymptotic distribution is proved to be chi-square under the null hypthesis and noncentral chi-square under an appropriate sequence of alternatives. For the optimal designs, the asymptotic relative efficiency of the proposed procedure with respect to the least squares procedure is the same as that of the Wilcoxon test with respect to the t-test.

• International Journal of Reliability and Applications
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• v.15 no.2
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• pp.99-110
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• 2014

Based on the kernel function, a new test is presented, testing $H_0:\bar{F}$ is exponential against $H_1:\bar{F}$ is UBACT and not exponential is given in section 2. Monte Carlos null distribution critical points for sample sizes n = 5(5)100 is investigated in section 3. The Pitman asymptotic efficiency for common alternatives is obtained in section 4. In section 5 we propose a test statistic for censored data. Finally, a numerical examples in medical science for complete and censored data using real data is presented in section 6.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.101-115
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• 2005

We propose in this article a procedure for testing unit and fractional orders of integration, with the roots simultaneously occurring in the trend, the seasonal and the cyclical component of the time series. The tests have standard null and local limit distributions. However, finite sample critical values are computed, and several Monte Carlo experiments conducted across the paper show that the rejection frequencies against unit (and fractional) orders of integration are relatively high in all cases. The tests are applied to the UK consumption and income series, the results showing the importance of the roots corresponding to the trend and the seasonal components and, though the unit roots are found to be fairly suitable models, we show that fractional processes (including one for the cyclical component) may also be plausible alternatives in some cases.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1053-1066
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• 2005

In this paper we consider the problem of identifying and testing outliers in linear regression. First we consider the use of the so-called scale ratio tests for testing the null hypothesis of no outliers. This test is based on the ratio of two residual scale estimates. We show the asymptotic distribution of the test statistics and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure using the suggested test is proposed. The new method is compared with classical procedure in the real data example. Unlike other forward procedures, the present one is unaffected by masking and swamping effects because the test statistic is based on robust scale estimate.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.11
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• pp.1511-1514
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• 2012

Epistasis that may explain a large portion of the phenotypic variation for complex economic traits of animals has been ignored in many genetic association studies. A Baysian method was introduced to draw inferences about multilocus genotypic effects based on their marginal posterior distributions by a Gibbs sampler. A simulation study was conducted to provide statistical powers under various unbalanced designs by using this method. Data were simulated by combined designs of number of loci, within genotype variance, and sample size in unbalanced designs with or without null combined genotype cells. Mean empirical statistical power was estimated for testing posterior mean estimate of combined genotype effect. A practical example for obtaining empirical statistical power estimates with a given sample size was provided under unbalanced designs. The empirical statistical powers would be useful for determining an optimal design when interactive associations of multiple loci with complex phenotypes were examined.

• Communications for Statistical Applications and Methods
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• v.29 no.3
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• pp.301-317
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• 2022

In this paper, we propose a change point detection procedure based on the modified information criterion in a generalized lambda distribution (GLD) model. Simulations are conducted to obtain empirical critical values of the proposed test statistic. We have also conducted simulations to evaluate the performance of the proposed methods comparing to the log-likelihood method in terms of power, coverage probability, and confidence sets. Our results indicate that, under various conditions, the proposed method modified information criterion (MIC) approach shows good finite sample properties. Furthermore, we propose a new goodness-of-fit testing procedure based on the energy distance to evaluate the asymptotic null distribution of our test statistic. Two real data applications are provided to illustrate the use of the proposed method.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.3
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• pp.131-142
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• 2018

Since income growth rate and poverty level are related, there is a possibility that the poverty rate may converge in the long run steady state as well. If the poverty rate converges, then for this study the state that begins with the high poverty rate would have a higher poverty reduction rate. To examine the convergence of poverty rate among the US states, this study uses two times series methodologies. First, in order to prevent the power loss from ignoring the structural break when testing for a unit root in a single time series, this study employs the newly developed panel LM unit root tests with level and trend shifts. The results of unit root tests of the log of poverty rate without allowing for structural breaks show that twenty six states reject the null hypothesis of unit root test for the ADF test, twenty five states for the LM test, and thirty five states for the RALS-LM test. The result of unit root tests that allow one structural break shows that the null hypothesis of a unit root test is rejected for twenty two states with the LM test, and thirty three states with the RALS-LM test. This supports poverty rates are converging among US states.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.4
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• pp.3-10
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• 2007

In this paper, we proposed the methodology for security testing using block-based file fault injection. When fault is inserted into software, we consider the format of file in order to efficiently reduce the error that is caused by mismatch of format of file. The Vulnerability the methodology focuses on is related to memory processing, such as buffer overflow, null pointer reference and so on. We implemented the automatic tool to apply the methodology to image file format and named the tool ImageDigger. We executed fault-injection focused on WMF and EMF file format using ImageDigger, and found 10 DOS(Denial of Service) in Windows Platform. This methodology can apply to block-based file format such as MS Office file.

• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.109-119
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• 1995

A two sample chi-square test is introduced for testing the equality of the distributions of two populations when observations are subject to random censorship. The statistic is appropriate in testing problems where a two-sided alternative is of interest. Under the null hypothesis, the asymptotic distribution of the statistic is a chi-square distribution. We obtain two types of chi-square statistics ; one as a nonnegative definite quadratic form in difference of observed cell probabilities based on the product-limit estimators, the other one as a summation form. Data pertaining to a cancer chemotheray experiment are examined with these statistics.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.283-292
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• 2013

This paper aims to propose a new steps of hypothesis testing using analysis process and improvement process in the six sigma DMAIC. The six sigma implementation models proposed in this paper consist of six steps. The first step is to establish a research hypothesis by specification directionality and FBP(Falsibility By Popper). The second step is to translate the research hypothesis such as RHAT(Research Hypothesis Absent Type) and RHPT(Research Hypothesis Present Type) into statistical hypothesis such as $H_0$(Null Hypothesis) and $H_1$(Alternative Hypothesis). The third step is to implement statistical hypothesis testing by PBC(Proof By Contradiction) and proper sample size. The fourth step is to interpret the result of statistical hypothesis test. The fifth step is to establish the best conditions of product and process conditions by experimental optimization and interval estimation. The sixth step is to draw a conclusion by considering practical significance and statistical significance. Important for both quality practitioners and academicians, case analysis on six sigma projects with implementation guidelines are provided.