• Communications for Statistical Applications and Methods
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• 제7권3호
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• pp.799-809
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• 2000

In this paper we propose a nonparametric one sided test for location parameters in p-variate(p$\geq$2) location translation model. The exact null distributions of test statistics are calculated by permutation principle in the case of relatively small sample sizes and the asymptotic distributions are also considered. The powers of various tests are compared through computer simulation and thep-values with real data are also suggested through example.

• Communications for Statistical Applications and Methods
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• 제11권3호
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• pp.597-607
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• 2004

The primary interest of drug development studies is identifying the lowest dose level producing a desirable effect over that of the zero-dose control, which is referred as the minimum effective dose (MED). In this paper, we suggest a nonparametric procedure for identifying the MED with binary or ordered categorical response data. Proposed test and Williams' test are compared by Monte Carlo simulation study and discussed.

• Communications for Statistical Applications and Methods
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• 제23권6호
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• pp.587-592
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• 2016

It is a long-standing issue to correctly determine the number of long-run relationships among time series processes. We revisit nonparametric test for cointegration rank and propose bootstrap refinements. Consistent with model-free nature of the tests, we make use of Cholesky factor bootstrap methods, which require weak conditions for data generating processes. Simulation studies show that the original Breitung's test have difficulty in obtaining the correct size due to dependence in cointegrated errors. Our proposed bootstrapped tests considerably mitigate size distortions and represent a complementary approach to other bootstrap refinements, including sieve methods.

• 응용통계연구
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• 제15권2호
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• pp.355-366
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• 2002

범주형 자료의 구조파악에 주로 이용되는 로짓모형에서 비모수적 방법을 이용한 모수의 신뢰구간추정과 가설검정 등의 통계적 추론에 대하여 살펴보았다. 모수에 대한 통계적 추론에서 정규분포에 근거한 모수적 방법(Wald 방법)보다는 붓스트랩 방법이나 임의순열을 활용한 비모수적 방법이 많이 활용되고 있다. 본 연구에서는 로짓모형의 모수에 대한 비모수적 추론방법으로 붓스트랩(bootstrap)과 임의순열(random permutation)의 두 방법을 고려하고 모의실험을 통하여 가설검정의 검정력과 신뢰구간추정의 포함확률을 비교하였고 사례분석을 다루었다.

• Communications for Statistical Applications and Methods
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• 제19권5호
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• pp.721-729
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• 2012

Various methods control the influence of a covariate on a response variable. These methods are analysis of covariance(ANCOVA), RANK ANCOVA, ANOVA of (covariate-adjusted) residuals, and Kruskal-Wallis tests on residuals. Covariate-adjusted residuals are obtained from the overall regression line fit to the entire data set that ignore the treatment levels or factors. It is demonstrated that the methods on covariate-adjusted residuals are only appropriate when the regression lines are parallel and covariate means are equal for all treatments. In this paper, we proposed the new nonparametric method on the ANCOVA model, as applying joint placement in a one-way layout on residuals as described in Chung and Kim (2007). A Monte Carlo simulation study is adapted to compare the power of the proposed procedure with those of the previous procedure.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.365-376
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• 2020

Interval-valued data, a type of symbolic data, is given as an interval in which the observation object is not a single value. It can also occur frequently in the process of aggregating large databases into a form that is easy to manage. Various regression methods for interval-valued data have been proposed relatively recently. In this paper, we introduce a nonparametric regression model using the kernel function and a nonlinear regression model for the interval-valued data. We also propose applying the local linear regression model, one of the nonparametric methods, to the interval-valued data. Simulations based on several distributions of the center point and the range are conducted using each of the methods presented in this paper. Various conditions confirm that the performance of the proposed local linear estimator is better than the others.

• Communications for Statistical Applications and Methods
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• 제9권3호
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• pp.607-618
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• 2002

Crossover design is often used in clinical trials about chronic diseases like hypertension, asthma and arthritis. In this paper, we suggest nonparametric approaches of Friedman-type rank test based on Bernard-van Elteren test and of aligned method keeping the information of blocks based on the AB/BA/AA/BB crossover design. The simulation results are presented to compare experimental error and power of several methods.

• Communications for Statistical Applications and Methods
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• 제26권1호
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• pp.57-67
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• 2019

Income distribution is a major concern in economic theory. In regional economics, it is often of interest to compare income distributions in different regions. Traditional methods often compare the income inequality of different regions by assuming parametric forms of the income distributions, or using summary statistics like the Gini coefficient. In this paper, we propose a nonparametric procedure to test for heterogeneity in income distributions among different regions, and a K-means clustering procedure for clustering income distributions based on energy distance. In simulation studies, it is shown that the energy distance based method has competitive results with other common methods in hypothesis testing, and the energy distance based clustering method performs well in the clustering problem. The proposed approaches are applied in analyzing data from China Health and Nutrition Survey 2011. The results indicate that there are significant differences among income distributions of the 12 provinces in the dataset. After applying a 4-means clustering algorithm, we obtained the clustering results of the income distributions in the 12 provinces.

• Communications for Statistical Applications and Methods
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• 제8권2호
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• pp.427-434
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• 2001

In this paper, we consider the nonparametric Bayesian approach to the multiple comparisons problem for I Poisson populations using Dirichlet process priors. We describe Gibbs sampling algorithm for calculating posterior probabilities for the hypotheses and calculate posterior probabilities for the hypotheses using Markov chain Monte Carlo. Also we provide a numerical example to illustrate the developed numerical technique.

• 한국전산구조공학회논문집
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• 제30권1호
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• pp.87-94
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• 2017

신뢰성 해석 및 신뢰성기반 최적설계는 불확실성을 고려한 확률변수를 입력 값으로 요구하며, 확률변수는 모수적 비모수적 통계모델링 방법을 사용하여 확률분포함수의 형태로 정량화 된다. 신뢰성 해석과 같은 통계적 해석은 입력되는 확률분포함수의 특성이 결과값에 영향을 미치게 되며, 확률분포함수는 통계모델링 방법에 따라 다른 형태를 가지게 된다. 본 연구에서는 모수적 통계모델링 방법인 순차적 통계모델링 방법과 비모수적 방법인 커널밀도추정을 사용하여 데이터의 개수에 따른 통계모델링의 결과를 분석하였다. 또한 수치예제를 통해 두 가지 기법에 따른 신뢰성 해석의 결과를 분석하였고, 데이터의 개수에 따른 적절한 기법을 제안하였다.