• Title/Summary/Keyword: Equivariance

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A Robust Estimator in Multivariate Regression Using Least Quartile Difference

  • Jung Kang-Mo
    • Communications for Statistical Applications and Methods
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    • v.12 no.1
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    • pp.39-46
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    • 2005
  • We propose an equivariant and robust estimator in multivariate regression model based on the least quartile difference (LQD) estimator in univariate regression. We call this estimator as the multivariate least quartile difference (MLQD) estimator. The MLQD estimator considers correlations among response variables and it can be shown that the proposed estimator has the appropriate equivariance properties defined in multivariate regressions. The MLQD estimator has high breakdown point as does the univariate LQD estimator. We develop an algorithm for MLQD estimate. Simulations are performed to compare the efficiencies of MLQD estimate with coordinatewise LQD estimate and the multivariate least trimmed squares estimate.

An Equivariant and Robust Estimator in Multivariate Regression Based on Least Trimmed Squares

  • Jung, Kang-Mo
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.1037-1046
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    • 2003
  • We propose an equivariant and robust estimator in multivariate regression model based on the least trimmed squares (LTS) estimator in univariate regression. We call this estimator as multivariate least trimmed squares (MLTS) estimator. The MLTS estimator considers correlations among response variables and it can be shown that the proposed estimator has the appropriate equivariance properties defined in multivariate regression. The MLTS estimator has high breakdown point as does LTS estimator in univariate case. We develop an algorithm for MLTS estimate. Simulation are performed to compare the efficiencies of MLTS estimate with coordinatewise LTS estimate and a numerical example is given to illustrate the effectiveness of MLTS estimate in multivariate regression.

A Comparison Study of Several Robust Regression Estimators under Various Contaminations (다양한 오염 상황에서의 여러 로버스트 회귀추정량의 비교연구)

  • 김지연;황진수;김진경
    • The Korean Journal of Applied Statistics
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    • v.17 no.3
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    • pp.475-488
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    • 2004
  • Several robust regression estimators are compared under contamination. Symmetric and asymmetric contamination schemes are used to measure the variance and MSE of regression estimators. Under asymmetric contamination depth-based regression estimator, especially projection based regression estimator(rcent) outperforms the rest and under symmetric contamination HBR performs relatively well.

Comparison of Parameter Estimation Methods in A Kappa Distribution

  • Jeong, Bo-Yoon;Park, Jeong-Soo
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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    • pp.163-169
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    • 2006
  • This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. The method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, ike dimensional nonlinear equations are simplied to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, the L-ME is recommended to use for small sample size $(n\leq100)$ while MLE is good for large sample size.

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Comparison of Parameter Estimation Methods in A Kappa Distribution

  • Park Jeong-Soo;Hwang Young-A
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.285-294
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    • 2005
  • This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. Method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, three dimensional nonlinear equations are simplified to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, L-ME (or MME) is recommended to use for small sample size( n$\le$100) while MLE is good for large sample size.

A Robust Test for Location Parameters in Multivariate Data (다변량 자료에서 위치모수에 대한 로버스트 검정)

  • So, Sun-Ha;Lee, Dong-Hee;Jung, Byoung-Cheo
    • The Korean Journal of Applied Statistics
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    • v.22 no.6
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    • pp.1355-1364
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    • 2009
  • This work propose a robust test for location parameters in multivariate data based on MVE and MCD with the affine equivariance and the high-breakdown properties. We consider the hypothesis testing satisfying high efficiency and high test power simultaneously to bring in the one-step reweighting procedure upon high-breakdown estimators, which generally suffer from the low efficiency and, as a result, usually used only in the exploratory analysis. Monte Carlo study shows that the suggested method retains nominal significance levels and higher testing power without regard to various population distributions than a Hotelling's $T^2$ test. In an example, a data set containing known outliers does not make an influence toward our proposal, while it renders a Hotelling's $T^2$ useless.

The consideration for methods of statistical analysis about the thesis published in the journal of korean oriental medical Ophthalmology & Otolaryngology & Dermatology from 2003 to 2005 (2003년부터 2005년까지 안이비인후피부과 학회지에 게재된 논문들의 통계적 분석 방법에 대한 고찰)

  • Kim, Keoo-Seok;Nam, Hae-Jung;Park, Owe-Suk;Kim, Hee-Jeong;Cha, Jae-Hoon;Kim, Yoon-Bum
    • The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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    • v.19 no.3 s.31
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    • pp.134-145
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    • 2006
  • Objective : This study was carried out to investigate what type of assumption and conditions are needed for the application of various statistical techniques such as descriptive statistics, t-test, analysis of variance, correlation analysis, regression analysis and chi-square test and to evaluate that they are used correctly in the research process. Methods : One more methods of statistical analysis were used in 91 papers among 162 papers selected from the journal of Korean oriental medical Ophthalmology & Otolaryngology & Dermatology from April 2003 to December 2005. So we analysed the type of statistical analysis method in 91 papers(clinical and experimental study) and assessed the their validity of statistical techniques by the check list consisting of 34 items(3 items for validity assessment of descriptive statistics, 6 items for t-test, 7 items for analysis of variance, correlation analysis and regression analysis, respectively, 4 items for chi-square test) Results : 1. The type of 65(40%) cases is experimental trial, the type of 55(34%) cases is case report, the type of 26(16%) cases is clinical trial and the type of 16(10%) cases is review, in 91 papers using statistical techniques among 162 papers selected from the journal of Korean oriental medical Ophthalmology & Otolaryngology & Dermatol-ogy from April 2003 to December 2005. 2. One more methods of statistical analysis were used in the experimental and clinical study. When we classified 125 units using statistical analysis methods in 91 papers according to statistical techniques such as descriptive statistics, t-test, analysis of variance, correlation analysis, regression analysis and chi-square test, the number of independent sample t-test is 33(26%), the number of only descriptive statistics is 28(22%), the number of independent sample t-test is 33(26%), the number of only descriptive statistics is 28(22%), the number of one way ANOVA is 15(12%), the number of non-parametric test 10(8%). 3. After carrying out one way ANOVA, the number of using multiple comparison methods is 15(Scheffe:6(26%), Duncan:4(17%), Dunnett:3(13%), Tukey:2(9%)) out of 23 (total case carrying out one way ANOVA). 8(35%) out of 23 did not enforce multiple comparison methods after carrying out one way ANOVA. 4. From the assessment of validity about 63 cases using statistical techniques(except descriptive statistics), 5(8%) cases are proper, the other 58(92%) are improper, so we recognized a serious misuse of statistical application in our journal. 5. The number of case below 10 sample size in experimental and clinical study(except descriptive statistics) is 31(34%) and frequent. Also the number of case containing no mention of sample size is 41(45%, including culture study). 6. For example of statistical error, there are wrong choice of statistical technique, lack of check on standard assumption(such as standard distribution, equivariance, independence), and so on. Conclusions : We investigated the validity of statistical analysis methods in our journal by check list consisting of 34 items and suggested correct statistical analysis methods. We should practice the spread of education about statistical analysis methods and precis application, enhance objectivity and reliability of our thesis and further correspond with purpose of scientific study.

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