• Title/Summary/Keyword: Permutation Test

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Tutorial: Methodologies for sufficient dimension reduction in regression

  • Yoo, Jae Keun
    • Communications for Statistical Applications and Methods
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    • v.23 no.2
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    • pp.105-117
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    • 2016
  • In the paper, as a sequence of the first tutorial, we discuss sufficient dimension reduction methodologies used to estimate central subspace (sliced inverse regression, sliced average variance estimation), central mean subspace (ordinary least square, principal Hessian direction, iterative Hessian transformation), and central $k^{th}$-moment subspace (covariance method). Large-sample tests to determine the structural dimensions of the three target subspaces are well derived in most of the methodologies; however, a permutation test (which does not require large-sample distributions) is introduced. The test can be applied to the methodologies discussed in the paper. Theoretical relationships among the sufficient dimension reduction methodologies are also investigated and real data analysis is presented for illustration purposes. A seeded dimension reduction approach is then introduced for the methodologies to apply to large p small n regressions.

Nonparametric Tests for Grouped K-Sample Problem

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.409-418
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    • 2006
  • We propose a nonparametric test procedure for the K-sample problem with grouped data. We construct the test statistics using the scores derived for the linear model based on likelihood ratio principle and obtain asymptotic distribution. Also we illustrate our procedure with an example. Finally we discuss some concluding remarks.

Bootstrapping and DNA Marker Mining of ILSTS098 Microsatellite Locus in Hanwoo Chromosome 2

  • Lee, Jea-Young;Kwon, Jae-Chul
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.525-535
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    • 2006
  • We describe tests for detecting and locating quantitative traits loci (QTL) for traits in Hanwoo. Lod scores and a permutation test have been described. From results of a permutation test to detect QTL, we select major DNA markers of ILSTS098 microsatellite locus in Hanwoo chromosome 2 for further analysis. K-means clustering analysis applied to four traits and eight DNA markers in ILSTS098 resulted in three cluster groups. We conclude that the major DNA markers of BMS1167 microsatellite locus in Hanwoo chromosome 2 are markers 105bp, 113bp and 115bp. Finally, bootstrap testing method has been adapted to calculate confidence intervals and for finding major DNA Markers.

한우 6번 염색체의 Bootstrap기법을 이용한 우수 DNA 탐색

  • Lee, Je-Yeong;Yeo, Jeong-Su;Kim, Jae-Woo;Lee, Yong-Won;Kim, Mun-Jeong
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.05a
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    • pp.41-47
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    • 2003
  • 한우 6번 염색체 유전자 지도에서 한우의 질을 높이기 위한 QTL(quantitative trait loci)분석을 실시하여 선별된 Loci 값을 Permutation Test를 이용하여 계산하였다. 한편, 경제적으로 주요한 한우의 특성부위(질적부위와 육량등)에 따른, 우수 경제형질 DNA marker를 K-평균 군집법을 실시 파악하였다. 이들 QTL과 K-평균법에 의해 한우의 염색체 6번, ILST035의 주요 경제 형질별 DNA marker들을 선별하여, Bootstrap BCa방법을 이용하여 각 DNA marker들의 신뢰구간을 구했다.

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Nonparametric two sample tests for scale parameters of multivariate distributions

  • Chavan, Atul R;Shirke, Digambar T
    • Communications for Statistical Applications and Methods
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    • v.27 no.4
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    • pp.397-412
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    • 2020
  • In this paper, a notion of data depth is used to propose nonparametric multivariate two sample tests for difference between scale parameters. Data depth can be used to measure the centrality or outlying-ness of the multivariate data point relative to data cloud. A difference in the scale parameters indicates the difference in the depth values of a multivariate data point. By observing this fact on a depth vs depth plot (DD-plot), we propose nonparametric multivariate two sample tests for scale parameters of multivariate distributions. The p-values of these proposed tests are obtained by using Fisher's permutation approach. The power performance of these proposed tests has been reported for few symmetric and skewed multivariate distributions with the existing tests. Illustration with real-life data is also provided.

A Study on the Bi-Aspect Test for the Two-Sample Problem

  • Hong, Seung-Man;Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.19 no.1
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    • pp.129-134
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    • 2012
  • In this paper we review a bi-aspect nonparametric test for the two-sample problem under the location translation model and propose a new one to accommodate a more broad class of underlying distributions. Then we compare the performance of our proposed test with other existing ones by obtaining empirical powers through a simulation study. Then we discuss some interesting features related to the bi-aspect test with a comment on a possible expansion for the proposed test as concluding remarks.

Bootstrap Median Tests for Right Censored Data

  • Park, Hyo-Il;Na, Jong-Hwa
    • Journal of the Korean Statistical Society
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    • v.29 no.4
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    • pp.423-433
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    • 2000
  • In this paper, we consider applying the bootstrap method to the median test procedures for right censored data. For doing this, we show that the median test statistics can be represented by the differences of two sampler medians. Then we review to the re-sampling methods for censored dta and propose the test procedures under the location translation assumption and Behrens-Fisher problem. Also we compare our procedures with other re-sampling method, which is so-called permutation test through an example. Finally we show the validity of bootstrap median test procedure in the appendix.

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Some versatile tests based on percentile tests

  • Park, Hyo-Il;Kim, Ju-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.2
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    • pp.291-296
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    • 2010
  • In this paper, we consider a versatile test based on percentile tests. The versatile test may be useful when the underlying distributions are unknown or quite different types. We consider two kinds of combining functions for the percentile statistics, the quadratic and summing forms and obtain the limiting distributions under the null hypothesis. Then we illustrate our procedure with an example. Finally we discuss some interesting features of the test as concluding remarks.

Some nonparametric test procedure for the multi-sample case

  • Park, Hyo-Il;Kim, Ju-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.1
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    • pp.237-250
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    • 2009
  • We consider a nonparametric test procedure for the multi-sample problem with grouped data. We construct the test statistics based on the scores obtained from the likelihood ratio principle and derive the limiting distribution under the null hypothesis. Also we illustrate our procedure with an example and obtain the asymptotic properties under the Pitman translation alternatives. Also we discuss some concluding remarks. Finally we derive the covariance between components in the Appendix.

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On the Study for the Simultaneous Test

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.20 no.4
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    • pp.241-246
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    • 2013
  • In this study, we propose a nonparametric simultaneous test procedure for the location translation and scale parameters. We consider the Wilcoxon rank sum test for the location translation parameter and the Mood test for the scale parameter with the quadratic and maximal types of combining functions. Then we derive the limiting null distributions of the combining functions. We illustrate our procedure with an example and compare efficiency by obtaining the empirical powers through a simulation study. Finally, we discuss some interesting features related to the nonparametric simultaneous tests.