• Title/Summary/Keyword: Bootstrap methods

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Development of Web-based Statistical System for Bootstrap on the Internet Environment (인터넷 환경에서 붓스트랩 통계 시스템의 개발)

  • 최성운;임인섭
    • Journal of the Korea Safety Management & Science
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    • v.6 no.2
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    • pp.241-250
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    • 2004
  • Recently, growth of internet causes rapid changes in many areas of statistics such as statistical computation and education. Especially, bootstrap is the most interesting statistical methods applying computer resampling simulation. In this study, we try to present how to use a method of bootstrap on the internet. We also develop to user a statistical system which is programed with java applet for user to handle easily.

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 Note on Parametric Bootstrap Model Selection

  • Lee, Kee-Won;Songyong Sim
    • Journal of the Korean Statistical Society
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    • v.27 no.4
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    • pp.397-405
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    • 1998
  • We develop parametric bootstrap model selection criteria in an example to fit a random sample to either a general normal distribution or a normal distribution with prespecified mean. We apply the bootstrap methods in two ways; one considers the direct substitution of estimated parameter for the unknown parameter, and the other focuses on the bias correction. These bootstrap model selection criteria are compared with AIC. We illustrate that all the selection rules reduce to the one sample t-test, where the cutoff points converge to some certain points as the sample size increases.

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Bootstrapping Logit Model

  • Kim, Dae-hak;Jeong, Hyeong-Chul
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.281-289
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    • 2002
  • In this paper, we considered an application of the bootstrap method for logit model. Estimation of type I error probability, the bootstrap p-values and bootstrap confidence intervals of parameter were proposed. Small sample Monte Carlo simulation were conducted in order to compare proposed method with existing normal theory based asymptotic method.

Development of Web-based Quality & Reliability System for Bootstrap on the Internet Environment (인터넷 환경에서 붓스트랩 품질 및 신뢰성 시스템의 개발)

  • Choi Sung woon;Lim In sup
    • Journal of the Korea Safety Management & Science
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    • v.7 no.1
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    • pp.147-157
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    • 2005
  • Recently, growth of internet causes rapid changes in many areas of statistics such as statistical computation and analysis. Especially, bootstrap is the most interesting statistical methods applying computer resampling simulation. In this paper, we try to present how to use a method of bootstrap on the internet. We also develop to user a statistical system which is programed with ASP for user to handle easily in manufacturing system.

Bootstrap Method for Row and Column Effects Model

  • Jeong, Hyeong-Chul
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.521-529
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    • 2005
  • In this paper, we consider a bootstrap method to the 'row and column effects model' (RC model) to analyze a contingency table with ordered variables. We propose a bootstrap procedure for testing of independence, equality of intervals, and goodness of fit in the RC model. A real data example is included.

Bootstrap Confidence Intervals for the Difference of Quantiles of Right Censored Data

  • Na, Jong-Hwa;Park, Hyo-Il;Jang, Young-Mi
    • Communications for Statistical Applications and Methods
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    • v.11 no.3
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    • pp.447-454
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    • 2004
  • In this paper, we consider the bootstrap method to the interval estimation of the difference of quantiles of right censored data. We showed the validity of bootstrap method and compare with others with real data example. In simulation various resampling schemes for right censored data are also considered.

Resampling Technique for Simulation Output Analysis

  • Kim, Yun-Bae
    • Journal of the Korea Society for Simulation
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    • v.1 no.1
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    • pp.31-36
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    • 1992
  • To estimate the probability of long delay in a queuing system using discrete-event simulation is studied. We contrast the coverage, half-width, and stability of confidence intervals constructed using two methods: batch means and new resampling technique; binary bootstrap. The binary bootstrap is an extension of the conventional bootstrap that resamples runs rather than data values. Empirical comparisons using known results for the M/M/1 and D/M/10 queues show the binary bootstrap superior to batch means for this problem.

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Resampling Technique for Simulation Output Analysis

  • Kim, Yun-Bae-
    • Proceedings of the Korea Society for Simulation Conference
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    • 1992.10a
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    • pp.13-13
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    • 1992
  • To estimate the probability of long delay in a queuing system using discrete-event simulation studied. We contrast the coverage, half-width, and stability of confidence intervals constructed using two methods: batch means and new resampling technique; binary bootstrap. The binary bootstrap is an extension of the conventional bootstrap that resamples runs rather than data values. Empirical comparisons using known results for the M/M/1 and D/M/10 queues show the binary bootstrap superior to batch means for this problem.

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Bootstrap Tests for the General Two-Sample Problem

  • Cho, Kil-Ho;Jeong, Seong-Hwa
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.1
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    • pp.129-137
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    • 2002
  • Two-sample problem is frequently discussed problem in statistics. In this paper we consider the hypothese methods for the general two-sample problem and suggest the bootstrap methods. And we show that the modified Kolmogorov-Smirnov test is more efficient than the Kolmogorov-Smirnov test.

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