• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.643-655
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• 2004

L$_1$-estimator in the linear regression model is widely recognized to have superior robustness in the presence of vertical outliers. While the L$_1$-estimation procedures and algorithms have been developed quite well, less progress has been made with the hypothesis test in the multiple L$_1$-regression. This article suggests computer-intensive resampling approaches, jackknife and bootstrap methods, to estimating the variance of L$_1$-estimator and the scale parameter that are required to compute the test statistics. Monte Carlo simulation studies are performed to measure the power of tests in small samples. The simulation results indicate that bootstrap estimation method is the most powerful one when it is employed to the likelihood ratio test.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1161-1168
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• 2011

The approximation for the distribution functions of nonparametric test statistics is a significant step in statistical inference. A rank sum test for dispersions proposed by Ansari and Bradley (1960), which is widely used to distinguish the variation between two populations, has been considered as one of the most popular nonparametric statistics. In this paper, the statistical tables for the distribution of the nonparametric Ansari-Bradley statistic is produced by use of polynomially adjusted normal approximation as a semi parametric density approximation technique. Polynomial adjustment can significantly improve approximation precision from normal approximation. The normal-polynomial density approximation for Ansari-Bradley statistic under finite sample sizes is utilized to provide the statistical table for various combination of its sample sizes. In order to find the optimal degree of polynomial adjustment of the proposed technique, the sum of squared probability mass function(PMF) difference between the exact distribution and its approximant is measured. It was observed that the approximation utilizing only two more moments of Ansari-Bradley statistic (in addition to the first two moments for normal approximation provide) more accurate approximations for various combinations of parameters. For instance, four degree polynomially adjusted normal approximant is about 117 times more accurate than normal approximation with respect to the sum of the squared PMF difference.

• 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.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.223-229
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• 1997

It is demonstrated that many standard nonparametric test such as the Mann-Whitney-Wilcoxon test, the Fisher-Yates test, the Savage test and the median test are admissible for a two-sample nonparametric testing problem. The admissibility of the Kruskal-Wallis test is demonstrated for a nonparametric one-way layout testing problem.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.19 no.3 s.31
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• pp.134-145
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• 2006

Objective : This study was carried out to investigate what type of assumption and conditions are needed for the application of various statistical techniques such as descriptive statistics, t-test, analysis of variance, correlation analysis, regression analysis and chi-square test and to evaluate that they are used correctly in the research process. Methods : One more methods of statistical analysis were used in 91 papers among 162 papers selected from the journal of Korean oriental medical Ophthalmology & Otolaryngology & Dermatology from April 2003 to December 2005. So we analysed the type of statistical analysis method in 91 papers(clinical and experimental study) and assessed the their validity of statistical techniques by the check list consisting of 34 items(3 items for validity assessment of descriptive statistics, 6 items for t-test, 7 items for analysis of variance, correlation analysis and regression analysis, respectively, 4 items for chi-square test) Results : 1. The type of 65(40%) cases is experimental trial, the type of 55(34%) cases is case report, the type of 26(16%) cases is clinical trial and the type of 16(10%) cases is review, in 91 papers using statistical techniques among 162 papers selected from the journal of Korean oriental medical Ophthalmology & Otolaryngology & Dermatol-ogy from April 2003 to December 2005. 2. One more methods of statistical analysis were used in the experimental and clinical study. When we classified 125 units using statistical analysis methods in 91 papers according to statistical techniques such as descriptive statistics, t-test, analysis of variance, correlation analysis, regression analysis and chi-square test, the number of independent sample t-test is 33(26%), the number of only descriptive statistics is 28(22%), the number of independent sample t-test is 33(26%), the number of only descriptive statistics is 28(22%), the number of one way ANOVA is 15(12%), the number of non-parametric test 10(8%). 3. After carrying out one way ANOVA, the number of using multiple comparison methods is 15(Scheffe:6(26%), Duncan:4(17%), Dunnett:3(13%), Tukey:2(9%)) out of 23 (total case carrying out one way ANOVA). 8(35%) out of 23 did not enforce multiple comparison methods after carrying out one way ANOVA. 4. From the assessment of validity about 63 cases using statistical techniques(except descriptive statistics), 5(8%) cases are proper, the other 58(92%) are improper, so we recognized a serious misuse of statistical application in our journal. 5. The number of case below 10 sample size in experimental and clinical study(except descriptive statistics) is 31(34%) and frequent. Also the number of case containing no mention of sample size is 41(45%, including culture study). 6. For example of statistical error, there are wrong choice of statistical technique, lack of check on standard assumption(such as standard distribution, equivariance, independence), and so on. Conclusions : We investigated the validity of statistical analysis methods in our journal by check list consisting of 34 items and suggested correct statistical analysis methods. We should practice the spread of education about statistical analysis methods and precis application, enhance objectivity and reliability of our thesis and further correspond with purpose of scientific study.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.341-353
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• 2008

The bootstrap method for the score test statistic is proposed in a bivariate negative binomial distribution. The Monte Carlo study shows that the score test for testing overdispersion underestimates the nominal significance level, while the score test for "intrinsic correlation" overestimates the nominal one. To overcome this problem, we propose a bootstrap method for the score test. We find that bootstrap methods keep the significance level close to the nominal significance level for testing the hypothesis. An empirical example is provided to illustrate the results.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.1-11
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• 2012

When the microarray experiment developed, main interest was limited to detect differentially expressed genes associated with a phenotype of interest. However, as human diseases are thought to occur through the interactions of multiple genes within a same functional category, the unit of analysis of the microarray experiment expanded to the set of genes. For the phenotype of censored survival time, Gene Set Enrichment Analysis(GSEA), Global test and Wald type test are widely used. In this paper, we modified the Wald type test by adopting normal score transformation of gene expression values and developed a parametric test which requires much less computation than others. The proposed method is compared with other methods using a real data set of ovarian cancer and a simulation data set.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.699-706
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• 2016

Outlier detection methods without performing a test often do not succeed in detecting multiple outliers because they are structurally vulnerable to a masking effect or a swamping effect. This paper considers testing procedures supplemented to a clustering-based method of identifying the group with a minority of the observations as outliers. One of general steps is performing a variety of t-test on individual outlier-candidates. This paper proposes a sequential procedure for searching for outliers by changing cutoff values on a cluster tree and performing a test on a set of outlier-candidates. The proposed method is illustrated and compared to existing methods by an example and Monte Carlo studies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.37-41
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• 2021

This study aims to investigate the relationship between the exchange rate and Trade Balance. Trade Balance is used as the dependent variable, and the independent variables are Exchange Rate, Gross Domestic Product, and Inflation. Augmented Dickey-Fuller unit root test was adopted to test the stationary property of time series data, Auto Regressive Distributed Lag model was employed to find the long run and short-run relationship and long-run adjustment, Bound test approach, the unrestricted Error Correction Model and Granger Causality Test are used to analyze the data from 1977 to 2019. The research findings suggest that inflation has a positive impact on the trade balance in the short run. The exchange rate and the Gross Domestic Product have adverse effects on Trade balance in the long run. The coefficient of ER in the previous year is negative, and the coefficient of TB in the previous year is positive and significant. This is consistent with the J-Curve phenomenon, which states that devaluation may not improve trade balance in the immediate period, but will significantly impact the trade balance improvement in subsequent periods. Hence Marshall Lerner Condition exists in Sri Lanka.

• Journal of the Korean Mathematical Society
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• v.52 no.3
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• pp.503-522
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• 2015

In this paper, we consider the problem of testing for a parameter change in nonlinear time series models with GARCH type errors. We introduce two types of cumulative sum (CUSUM) tests: estimates-based and residual-based tests. It is shown that under regularity conditions, their limiting null distributions are the sup of independent Brownian bridges. A simulation study is conducted for illustration.