• 제목/요약/키워드: Performance-based Statistics

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On the Performance of Empiricla Bayes Simultaneous Interval Estimates for All Pairwise Comparisons

  • Kim, Woo-Chul;Han, Kyung-Soo
    • Journal of the Korean Statistical Society
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    • 제24권1호
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    • pp.161-181
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    • 1995
  • The goal of this article is to study the performances of various empirical Bayes simultaneous interval estimates for all pairwise comparisons. The considered empirical Bayes interval estimaters are those based on unbiased estimate, a hierarchical Bayes estimate and a constrained hierarchical Bayes estimate. Simulation results for small sample cases are given and an illustrative example is also provided.

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Comparative Study of Confidence Intervals for Relative Ratio

  • Park, Sang-Gue;Oh, You-Jin
    • Communications for Statistical Applications and Methods
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    • 제6권2호
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    • pp.621-634
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    • 1999
  • Consider the several methods of constructing interval for relative ration from two independent binomial samples. The special interests are gives in the cases of low rates and small samples. bias-corrected and accelerated bootstrap method is proposed to overcome are the non-efficiency of current methods based on asymptotic resuts. Simulation studies are presented to demonstrate the performance of the proposed method.

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Test for Parameter Changes in the AR(1) Process

  • Kim, Soo-Hwa;Cho, Sin-Sup;Park, Young J.
    • Journal of the Korean Statistical Society
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    • 제26권3호
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    • pp.417-427
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    • 1997
  • In this paper the parameter change problem in the stationary time series is considered. We propose a cumulative sum (CUSUM) of squares-type test statistic for detection of parameter changes in the AR(1) process. The proposed test statistic is based on the CUSIM of the squared observations and is shown to converge to a standard Brownian bridge. Simulations are performed to evaluate the performance of the proposed statistic and a real example is provided to illustrate the procedure.

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Measuring the Long-run Stock Returns to Investors

  • Choi, Seung-Doo
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2002년도 춘계학술대회
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    • pp.75-84
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    • 2002
  • This paper compares long-run returns of privatization initial public offerings to those of domestic stock markets of respective countries using a sample of 196 privatization initial public offerings from 39 countries. The evidence indicates that the privatization initial public offerings (IPOs) significantly outperform their domestic stock markets. There are substantial differences in the long-run performance of privatization IPOs depending on the return estimation techniques, however. Evidence indicates that the inference based either on conventional t or on skewness-adjusted t statistics may yield misspecified test statistics. The quality of estimation tends to be improved by simply eliminating the outliers from the sample, especially for the buy-and-hold abnormal return technique.

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Demerit-EWMA Control Charts

  • 조교영;전영목
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2004년도 춘계학술대회
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    • pp.7-14
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    • 2004
  • In this paper, we present an effective method for process control using the Demerit-EWMA control chart in the process where nonconforming units or nonconformities are occurred by various types. We compare performance of Demerit control chart, Demerit-CUSUM control chart and Demerit-EWMA control chart based on the average run length.

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Improvement of SOM using Stratification

  • Jun, Sung-Hae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제9권1호
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    • pp.36-41
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    • 2009
  • Self organizing map(SOM) is one of the unsupervised methods based on the competitive learning. Many clustering works have been performed using SOM. It has offered the data visualization according to its result. The visualized result has been used for decision process of descriptive data mining as exploratory data analysis. In this paper we propose improvement of SOM using stratified sampling of statistics. The stratification leads to improve the performance of SOM. To verify improvement of our study, we make comparative experiments using the data sets form UCI machine learning repository and simulation data.

A Comparative Study of Assessing Average Bioequivalence in $2{\times}2$ Crossover Design with Missing Observations

  • Park, Sang-Gue;Choi, Ji-Yun
    • Journal of the Korean Data and Information Science Society
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    • 제17권1호
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    • pp.245-257
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    • 2006
  • A modified Anderson and Hauck(1983) test for analyzing a two-sequence two-period crossover design in bioequivalence trials is proposed when some observations at the second period are missing. It is based on the maximum likelihood estimators of average bioequivalence model and designed for handling missing at random(MAR) situation. The performance of the proposed test is compared to other tests using Monte Carlo simulations.

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Variable Bandwidth Selection for Kernel Regression

  • Kim, Dae-Hak
    • Journal of the Korean Data and Information Science Society
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    • 제5권1호
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    • pp.11-20
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    • 1994
  • In recent years, nonparametric kernel estimation of regresion function are abundant and widely applicable to many areas of statistics. Most of modern researches concerned with the fixed global bandwidth selection which can be used in the estimation of regression function with all the same value for all x. In this paper, we propose a method for selecting locally varing bandwidth based on bootstrap method in kernel estimation of fixed design regression. Performance of proposed bandwidth selection method for finite sample case is conducted via Monte Carlo simulation study.

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A Study of Demerit-EWMA Control Charts

  • Cho, Gyo-Young;Jeon, Young-Mok
    • Journal of the Korean Data and Information Science Society
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    • 제15권2호
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    • pp.431-439
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    • 2004
  • In this paper, we present an effective method for process control using the Demerit-EWMA control chart in the process where nonconforming units or nonconformities are occurred by various types. We compare performance of Demerit control chart, Demerit-CUSUM control chart and Demerit-EWMA control chart based on the average run length(ARL).

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Bayesian Estimation of the Normal Means under Model Perturbation

  • Kim, Dal-Ho;Han, Seung-Cheol
    • Journal of the Korean Data and Information Science Society
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    • 제17권3호
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    • pp.1009-1019
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    • 2006
  • In this paper, we consider the simultaneous estimation problem for the normal means. We set up the model structure using the several different distributions of the errors for observing their effects of model perturbation for the error terms in obtaining the empirical Bayes and hierarchical Bayes estimators. We compare the performance of those estimators under model perturbation based on a simulation study.

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