• 제목/요약/키워드: nonparametric statistic

검색결과 82건 처리시간 0.027초

A STUDY ON A NONPARAMETRIC TEST FOR THE PARALLELISM OF k REGRESSION LINES AGAINST ORDERED ALTERNATIVES

  • Jee, Eun-Sook
    • Journal of applied mathematics & informatics
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    • 제8권2호
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    • pp.669-682
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    • 2001
  • In this paper a nonparametric test for the parallelism of k regression lines against ordered alternatives, when the independent variables are positive and all regression lines have a common intercept is proposed. The proposed test is based on a Jonckheere-type statistic applied to residuals. Under some conditions the proposed test statistic is asymptotically distribution-free. The small-sample powers of our test are compared with other tests by a Monte Carlo study. The simulation results show that the proposed test has significantly higher empirical powers than the other tests considered in this paper.

Data-Driven Smooth Goodness of Fit Test by Nonparametric Function Estimation

  • Kim, Jongtae
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.811-816
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    • 2000
  • The purpose of this paper is to study of data-driven smoothing goodness of it test, when the hypothesis is complete. The smoothing goodness of fit test statistic by nonparametric function estimation techniques is proposed in this paper. The results of simulation studies for he powers of show that the proposed test statistic compared well to other.

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Nonparametric Granger Causality Test

  • Jeong, Ki-ho;Nishiyama, Yoshihiko
    • Journal of the Korean Data and Information Science Society
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    • 제18권1호
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    • pp.195-210
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    • 2007
  • This paper develops a consistent nonparametric test for Granger causality in the context of strong-mixing process, which covers a large class of stationary processes including ARMA and ARCH models. The previously proposed tests require absolute regularity ($\beta$-mixing) more stringent than the strong-mixing condition. We prove the consistency of the test under a high level assumption on the approximation error of U statistic by its projection. Due to the sample splitting, the test statistic we propose is asymptotically normally distributed under the null.

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회귀직선 기울기의 순서성에 대한 비모수적 검정법 (A nonparametric test for parallelism of regression lines against ordered alternatives)

  • 송문섭;이기훈;김순옥
    • 응용통계연구
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    • 제6권2호
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    • pp.401-408
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    • 1993
  • 본 논문에서는 회귀직선 기울기의 순서성에 대한 비모수적 검정법을 제안하였다. 자료의 정보를 최대한 활용하는 Potthoff 형태의 검정통계량을 붓스트랩 분산추정량으로 표준화하여 점근 분포무관 검정을 한다. 또한 제안된 검정법의 특성과 효율을 대표본과 소표본에서 비교연구하였다.

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A Nonparametric Bootstrap Test and Estimation for Change

  • Kim, Jae-Hee
    • Communications for Statistical Applications and Methods
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    • 제14권2호
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    • pp.443-457
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    • 2007
  • This paper deals with the problem of testing the existence of change in mean and estimating the change-point using nonparametric bootstrap technique. A test statistic using Gombay and Horvath (1990)'s functional form is applied to derive a test statistic and nonparametric change-point estimator with bootstrapping idea. Achieved significance level of the test is calculated for the proposed test to show the evidence against the null hypothesis. MSE and percentiles of the bootstrap change-point estimators are given to show the distribution of the proposed estimator in simulation.

Statistical Bias and Inflated Variance in the Genehunter Nonparametric Linkage Test Statistic

  • Song, Hae-Hiang;Choi, Eun-Kyeong
    • Communications for Statistical Applications and Methods
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    • 제16권2호
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    • pp.373-381
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    • 2009
  • Evidence of linkage is expressed as a decreasing trend of the squared trait difference of two siblings with increasing identical by descent scores. In contrast to successes in the application of a parametric approach of Haseman-Elston regression, notably low powers are demonstrated in the nonparametric linkage analysis methods for complex traits and diseases with sib-pairs data. We report that the Genehunter nonparametric linkage statistic is biased and furthermore the variance formula that they used is an inflated one, and this is one reason for a low performance. Thus, we propose bias-corrected nonparametric linkage statistics. Simulation studies comparing our proposed nonparametric test statistics versus the existing test statistics suggest that the bias-corrected new nonparametric test statistics are more powerful and attains efficiencies close to that of Haseman-Elston regression.

집단관측치에 의한 비모수적 축차검정에 관한 연구 (A nonparametric sequential test based on observations in groups)

  • 박창순
    • 응용통계연구
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    • 제1권2호
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    • pp.66-81
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    • 1987
  • 이 연구에서는 새로운 방법의 비모수적 축차검정방법이 제시되었다. 먼저 축차적으로 얻어지는 관측치를 일정수의 집단으로 분류하고 각집단으로부터 주어진 가설에 적절한 비모수 통계량을 구하여 이것을 축차확률비검정에서 사용되는 로그확률비통계량에 대체하여 Wald의 축차검정을 수행하는 방법이다. 이러한 검정의 특성은 Wiener과정에 의해 근사적으로 규명되었다.

A Simple Nonparametric Test of Complete Independence

  • Park, Cheol-Yong
    • 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.

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확률화 블록 실험계획 모형에서 검정 통계량들의 검정력 분석 (The Analysis of power of the Test Statistics for the Randomized Block Design)

  • 배현웅;김제영
    • 한국국방경영분석학회지
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    • 제27권2호
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    • pp.124-133
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    • 2001
  • The purpose of this study is investigate the differences among parametric and nonparametric test statistics for the tree alternative hypothesis in the randomized block design. As the results, it was found that there was no large differences among parametric and nonparametric test statistics in power when the block sizes were larger, and Hollander's statistic had better power than other nonparametric test statistics. It is recommended that Hollander's test statistic is more useful method when we have no information about the distribution of population.

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Asymptotic Distribution of a Nonparametric Multivariate Test Statistic for Independence

  • 엄용환
    • Journal of the Korean Data and Information Science Society
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    • 제12권1호
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    • pp.135-142
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    • 2001
  • A multivariate statistic based on interdirection is proposed for detecting dependence among many vectors. The asymptotic distribution of the proposed statistic is derived under the null hypothesis of independence. Also we find the asymptotic distribution under the alternatives contiguous to the null hypothesis, which is needed for later use of computing relative efficiencies.

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