• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.401-411
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• 2013

This study investigates the controversial chickens-eggs dilemma and empirically performs statistical tests to examine if there exists a causality between them. Granger and Hsiao tests are applied to both level and stationary variables to identify the lead-lag relationships. Each of these test is found to have the robust result where the causality runs from eggs to chickens; in addition, the explanatory power of one variable in variations of the other appears to remain time invariant. The outcome is proved to be valid as the hypothesis test for no structural change in their relationship fails to be rejected.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.431-443
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• 2019

Goodness-of-fit techniques are an important topic in statistical analysis. Censored data occur frequently in survival experiments; therefore, many studies are conducted when data are censored. In this paper we mainly consider test statistics based on the empirical distribution function (EDF) to test normal distributions with unknown location and scale parameters when data are randomly censored. The most famous EDF test statistic is the Kolmogorov-Smirnov; in addition, the quadratic statistics such as the $Cram{\acute{e}}r-von$ Mises and the Anderson-Darling statistic are well known. The $Cram{\acute{e}}r-von$ Mises statistic is generalized to randomly censored cases by Koziol and Green (Biometrika, 63, 465-474, 1976). In this paper, we generalize the Anderson-Darling statistic to randomly censored data using the Kaplan-Meier estimator as it was done by Koziol and Green. A simulation study is conducted under a particular censorship model proposed by Koziol and Green. Through a simulation study, the generalized Anderson-Darling statistic shows the best power against almost all alternatives considered among the three EDF statistics we take into account.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.653-660
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• 2003

In this paper, we prove that the transformed sample Lorenz curve, normalized sample Lorenz curve, and the test statistics for testing of normality based on the normalized sample Lorenz curve and the modified Lorenz curve which were introduced by Kang and Cho (2001a, 2002) are location and scale invariant statistics.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.33-36
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• 1999

This paper proposes a mathematical model for the statistics of the W-CDMA signals with different bandwidth. Based on the statistics of numerically generated signals, a mathematical model is obtained such as Rayleigh, Rician, and Maxwell distribution. We employ Chi-square test to verify the fitness of the mathematical model with signal statistics. The results show obviously that the new proposed model is useful for representing W-CDMA signals.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.13-15
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• 2005

In this paper, we propose an extension of the maximum likelihood seasonal cointegration procedure developed by Johansen and Schaumburg (1999) for daily time series. We presented the finite sample distribution of the associated rank test statistics for daily data.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.1-11
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• 2014

The Weighted Logrank test and its special case, Logrank test are widely used to compare survival distributions; however, these methods are inappropriate when the sample size is small or censoring distributions are not equal since they use test statistics from approximate distributions. A permutation test can be an alternative for small sample cases; however, this should be used only when censoring distributions are equal. To handle cases with small sample size and unequal censoring distributions, the permutation-imputation method was developed to compare two survival distributions. In this paper, approximate method, permutation method and permutation-imputation method were compared using a Logrank test and Prentice-Wilcoxon test for three or more survival distributions comparison.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.579-590
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• 2017

The multivariate empirical distribution function could be defined when its distribution function can be estimated. It is known that bivariate empirical distribution functions could be visualized by using Step plot and Quantile plot. In this paper, the multivariate empirical distribution plot is proposed to represent the multivariate empirical distribution function on the unit square. Based on many kinds of empirical distribution plots corresponding to various multivariate normal distributions and other specific distributions, it is found that the empirical distribution plot also depends sensitively on its distribution function and correlation coefficients. Hence, we could suggest five goodness-of-fit test statistics. These critical values are obtained by Monte Carlo simulation. We explore that these critical values are not much different from those in text books. Therefore, we may conclude that the proposed test statistics in this work would be used with known critical values with ease.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.853-863
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• 2010

The performance test in a public survey is conducted by a sample survey and the sampling rate of the performance test is a very important factor in the test process. Since the current sampling rate was decided empirically at an earlier time, it has been criticized for two points: the first is that it has a lack of a theoretical background on the decision for the sampling rate and the second is that the sampling rate should be improved in accordance with current test situations. In this paper, we review the present state of performance tests in public surveys in Korea and study the relationship between the rate of the performance test and fitness probability, number of tests, and the success rate in order to create a theoretical background to improve the test rate. In addition, we discuss relationship between the test rate and cost in the performance test.

• Journal of Korean Society for Quality Management
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• v.23 no.4
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• pp.52-57
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• 1995

Testing problem of equality between two linear regressions is considered. Chow test is discussed and likelihood ratio test(LR test), F-test and Score test are derived. Score test are compared with other tests and show they are asymptotically equivalent.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.495-500
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• 2012

We consider a Bayesian test of independence in a two-way contingency table that has some zero cells. To do this, we take a three-stage hierarchical Bayesian model under each hypothesis. For prior, we use Dirichlet density to model the marginal cell and each cell probabilities. Our method does not require complicated computation such as a Metropolis-Hastings algorithm to draw samples from each posterior density of parameters. We draw samples using a Gibbs sampler with a grid method. For complicated posterior formulas, we apply the Monte-Carlo integration and the sampling important resampling algorithm. We compare the values of the Bayes factor with the results of a chi-square test and the likelihood ratio test.