• Communications for Statistical Applications and Methods
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• 제23권3호
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• pp.215-230
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• 2016

The powers of some tests for independence hypothesis against positive (negative) quadrant dependence in generalized Farlie-Gumbel-Morgenstern distribution are compared graphically by simulation. Some of these tests are usual linear rank tests of independence. Two other possible rank tests of independence are locally most powerful rank test and a powerful nonparametric test based on the $Cram{\acute{e}}r-von$ Mises statistic. We also evaluate the empirical power of the class of distribution-free tests proposed by Kochar and Gupta (1987) based on the asymptotic distribution of a U-statistic and the test statistic proposed by $G{\ddot{u}}ven$ and Kotz (2008) in generalized Farlie-Gumbel-Morgenstern distribution. Tests of independence are also compared for sample sizes n = 20, 30, 50, empirically. Finally, we apply two examples to illustrate the results.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 춘계학술대회
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• pp.121-126
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• 2003

In this paper, we consider two-components system which the lifetimes follow bivariate pareto model with censored data. We develop large sample tests for testing independence between two-components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

• Communications for Statistical Applications and Methods
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• 제6권2호
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• pp.565-584
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• 1999

the covariance process of two martingales provides a useful tool to capture the dependence structure for paired censored data. in this paper it is applied to modify the variances of weighted logrank tests in order to take account of dependence between paired subjects. In the process of modification a 'variance correction term' is introduced. Some variance estimators based on separate samples are considered together. Performance of the estimators are compared through simulation studies. Several independence tests for bivariate sruvival date are also proposed which are naturally reduced from the weighted logrank tests accomodating dependence structure. Simulation studies are carried out to compare the independence tests. Both the weighted logrank tests and the independence tests are illustrated by an example.

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1039-1055
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• 2014

검정통계량의 영가설 분포는 모집단 분포에 의존하는데 모집단의 분포를 모를 때 영가설 분포를 검정통계량의 조건부 분포로 대체하여 검정하는 방법을 순열 검정이라고 한다. Strasser와 Weber (1999)는 순열 검정을 통합하는 이론을 마련하였고, Hothorn 등 (2006, 2008)은 그 이론을 R에 내장된 coin 패키지에 구현하였다. coin 패키지에서 조건부 독립성 검정은 총괄적인 형태의 함수인 independence test를 통해서 할 수 있지만 대표적인 독립성 검정은 사용자가 편리하도록 간편한 함수를 별도로 제공하고 있다. 본 논문에서는 Strasser와 Weber (1999)의 순열 검정 방법에 대해 소개하고, coin 패키지에 내장된 15개의 간편 함수에 대해 independence test 함수로 변환하는 절차를 설명하고자 한다. 또한, 정의한 independence test 함수를 써서 실제 자료의 점근 분포와 순열 검정, 정확 검정에 기초한 p-값을 서로 비교하고자 한다.

• Communications for Statistical Applications and Methods
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• 제5권2호
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• pp.411-416
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• 1998

A simple nonparametric test of complete or total independence is suggested for continuous multivariate distributions. This procedure first discretizes the original variables based on their order statistics, and then tests the hypothesis of complete independence for the resulting contingency table. Under the hypothesis of independence, the chi-squared test statistic has an asymptotic chi-squared distribution. We present a simulation study to illustrate the accuracy in finite samples of the limiting distribution of the test statistic. We compare our method to another nonparametric test of complete independence via a simulation study. Finally, we apply our method to the residuals from a real data set.

• Communications for Statistical Applications and Methods
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• 제17권4호
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• pp.493-505
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• 2010

Developing a test for independence of random variables X and Y against the alternative has an important role in statistical inference. Kochar and Gupta (1987) proposed a class of tests in view of Block and Basu (1974) model and compared the powers for sample sizes n = 8, 12. In this paper, we evaluate Kochar and Gupta (1987) class of tests for testing independence against quadrant dependence in absolutely continuous bivariate Farlie-Gambel-Morgenstern distribution, via a simulation study for sample sizes n = 6, 8, 10, 12, 16 and 20. Furthermore, we compare the power of the tests with that proposed by G$\ddot{u}$uven and Kotz (2008) based on the asymptotic distribution of the test statistics.

• Journal of the Korean Data and Information Science Society
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• 제26권4호
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• pp.971-984
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• 2015

Imputation procedures fill-in missing values, thereby enabling complete data analyses. Fully efficient fractional imputation (FEFI) and multiple imputation (MI) create multiple versions of the missing observations, thereby reflecting uncertainty about their true values. Methods have been described for hypothesis testing with multiple imputation. Fractional imputation assigns weights to the observed data to compensate for missing values. The focus of this article is the development of tests of independence using FEFI for partially classified two-way contingency tables. Wald and deviance tests of independence under FEFI are proposed. Simulations are used to compare type I error rates and Power. The partially observed marginal information is useful for estimating the joint distribution of cell probabilities, but it is not useful for testing association. FEFI compares favorably to other methods in simulations.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.377-383
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• 2003

In this paper, we consider two components system in which the lifetimes follow the bivariate Pareto model with random censored data. We assume that the censoring time is independent of the lifetimes of the two components. We develop large sample tests for testing independence between two components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

• Communications for Statistical Applications and Methods
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• 제29권5호
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• pp.547-559
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• 2022

For a chi-squared test, which is a statistical method used to test the independence of a contingency table of two factors, the expected frequency of each cell must be greater than 5. The percentage of cells with an expected frequency below 5 must be less than 20% of all cells. However, there are many cases in which the regional expected frequency is below 5 in general small area studies. Even in large-scale surveys, it is difficult to forecast the expected frequency to be greater than 5 when there is small area estimation with subgroup analysis. Another statistical method to test independence is to use the Bayes factor, but since there is a high ratio of data dependency due to the nature of the Bayesian approach, the low expected frequency tends to decrease the precision of the test results. To overcome these limitations, we will borrow information from areas with similar characteristics and pool the data statistically to propose a pooled Bayes test of independence in target areas. Jo et al. (2021) suggested hierarchical Bayesian pooling models for small area estimation of categorical data, and we will introduce the pooled Bayes factors calculated by expanding their restricted pooling model. We applied the pooled Bayes factors using bone mineral density and body mass index data from the Third National Health and Nutrition Examination Survey conducted in the United States and compared them with chi-squared tests often used in tests of independence.

• 응용통계연구
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• 제28권6호
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• pp.1245-1255
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• 2015

본 논문에서는 한국 유가증권시장의 시가총액 상위 8개사 주가 수익률 절대값(absolute return)을 이용하여, 분포의 적합도 검정(goodness of fit test) 및 기업들 간의 독립성 검정(independence test)을 실시하였다. 검정 결과 개별 주가 수익률은 압축된 지수분포(compressed exponential distribution)를 이루는 것으로 나타났다. 이 때 파라미터는 1 < ${\beta}$ < 2 인 경우가 ${\beta}=1$(지수분포), ${\beta}=2$(정규분포)보다 우세한 것으로 확인되었다. 한편 독립성 검정에서는 대부분의 기업들이 관련성을 지니고 있는 것으로 나타났다.