• Title/Summary/Keyword: Statistical Procedures

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A Note on Comparing Multistage Procedures for Fixed-Width Confidence Interval

  • Choi, Ki-Heon
    • Communications for Statistical Applications and Methods
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    • v.15 no.5
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    • pp.643-653
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    • 2008
  • Application of the bootstrap to problems in multistage inference procedures are discussed in normal and other related models. After a general introduction to these procedures, here we explore in multistage fixed precision inference in models. We present numerical comparisons of these procedures based on bootstrap critical points for small and moderate sample sizes obtained via extensive sets of simulated experiments. It is expected that the procedure based on bootstrap leads to better results.

SELECTION PROCEDURES TO SELECT POPULATIONS BETTER THAN A CONTROL

  • Kumar, Narinder;Khamnel, H.J.
    • Journal of the Korean Statistical Society
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    • v.32 no.2
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    • pp.151-162
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    • 2003
  • In this paper, we propose two selection procedures for selecting populations better than a control population. The bestness is defined in terms of location parameter. One of the procedures is based on two-sample linear rank statistics whereas the other one is based on a comparatively simple statistic, and is useful when testing time is expensive so that an early termination of an experiment is desirable. The proposed selection procedures are seen to be strongly monotone. Performance of the proposed procedures is assessed through simulation study.

Application Guide of Reliability Test (신뢰성 시험 적용 모델)

  • Choi, Sung-Woon
    • Proceedings of the Safety Management and Science Conference
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    • 2007.04a
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    • pp.295-307
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    • 2007
  • This paper introduces statistical test principles, statistical procedures and tests for exponential distribution. This paper also shows compliance test plans for success ratio and constant failure rate, and goodness-of-fit tests for Weibull distribution. Moreover, this paper presents procedures for comparision of two constant failure rates, and dependability of products containing reused parts.

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Subset Selection Procedures Based on Some Robust Estimators

  • Song, Moon-Sub;Chung, Han-Yeong;Bae, Wha-Soo
    • Journal of the Korean Statistical Society
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    • v.11 no.2
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    • pp.109-117
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    • 1982
  • In this paper, a preliminary study is performed on the subset selection procedures which are based on the trimmed means and the Hodges-Lehmann estimator derived from the Wilcoxon test. The proposed procedures are compared to the Gupta's rule through a small smaple Monte Carlo study. The results show that the procedures based on the robust estimators are successful in terms of efficiency and robustness.

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A Study on Nonparametric Selection Procedures for Scale Parameters

  • Song, Moon-Sup;Chung, Han-Young;Kim, Dong-Jae
    • Journal of the Korean Statistical Society
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    • v.14 no.1
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    • pp.39-47
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    • 1985
  • In this paper, we propose some nonparametric subset selection procedures for scale parameters based on rank-likes. The proposed procedures are compared to the Gupta-Sobel's parametric prcedure through a small-sample Monte Carlo study. The results show that the nonparametric procedures are quite robust for heavy-tailed distributions, but they have somewhat low efficiencies.

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Two Sample Tests in the Weibull Distribution

  • Park, Won-Joon
    • Journal of the Korean Statistical Society
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    • v.8 no.2
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    • pp.99-105
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    • 1979
  • In Thoman and Bain and Schafer and Sheffield, procedures for testing the equality of the scale parameters of two Weibull populations with a common shape parameter and procedures for selecting the Weibull population with the largest scale parameter are given. We give, in this paper, a modified procedure for the above testing and selection problems, which is more powerful than those previoulsy given.

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Nonparametric Procedures for Finding Minimum Effective Dose in a One-Way Layout

  • Kim, Hyeonjeong;Kim, Dongjae
    • Communications for Statistical Applications and Methods
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    • v.9 no.3
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    • pp.693-701
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    • 2002
  • When the lowest dose level compared with zero-dose control has significant difference in effect, it is referred as minimum effective dose (MED). In this paper, we discuss several nonparametric methods for finding MED using updated rank at each sequential test step in small sample size and suggest new nonparametric procedures based on placement. Monte Carlo Simulation is adapted to compare power and Familywise Error Rate(FWE) of the new procedures with those of discussed nonparametric tests for finding MED.

A Comparison of Distribution-free Two-sample Procedures Based on Placements or Ranks

  • Kim, Dong-Jae
    • Journal of the Korean Statistical Society
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    • v.23 no.1
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    • pp.135-149
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    • 1994
  • We discussed a comparison of distribution-free two-sample procedures based on placements or ranks. Iterative asymptotic distribution of both two-sample procedures is studies and small sample Monte Carlo simulation results are presented. Also, we proposed the Hodges-Lehmann type location estimator based on linear placement statistics.

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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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A Bayesian Hypothesis Testing Procedure Possessing the Concept of Significance Level

  • Hwang, Hyungtae
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.787-795
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    • 2001
  • In this paper, Bayesian hypothesis testing procedures are proposed under the non-informative prior distributions, which can be thought as the Bayesian counterparts of the classical ones in the sense of using the concept of significance level. The performances of proposed procedures are compared with those of classical procedures through several examples.

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