• 제목/요약/키워드: BOOTSTRAP

검색결과 686건 처리시간 0.037초

A Simulation Study for the Confidence Intervals of p by Using Average Coverage Probability

  • Kim, Daehak;Jeong, Hyeong-Chul
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.859-869
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    • 2000
  • In this paper, various methods for finding confidence intervals for p of binomial parameter are reviewed. Also we introduce tow bootstrap confidence intervals for p. We compare the performance of bootstrap methods with other methods in terms of average coverage probability by Monte Carlo simulation. Advantages of these bootstrap methods are discussed.

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

  • 최성운;임인섭
    • 대한안전경영과학회지
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    • 제7권1호
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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.

Empirical Bayes Confidence Intervals of the Burr Type XII Failure Model

  • Choi, Dal-Woo
    • Journal of the Korean Data and Information Science Society
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    • 제10권1호
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    • pp.155-162
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    • 1999
  • This paper is concerned with the empirical Bayes estimation of one of the two shape parameters(${\theta}$) in the Burr(${\beta},\;{\theta}$) type XII failure model based on type-II censored data. We obtain the bootstrap empirical Bayes confidence intervals of ${\theta}$ by the parametric bootstrap introduced by Laird and Louis(1987). The comparisons among the bootstrap and the naive empirical Bayes confidence intervals through Monte Carlo study are also presented.

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Interval Estimations for Reliablility in Stress-Strength Model by Bootstrap Method

  • Lee, In-Suk;Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • 제6권1호
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    • pp.73-83
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    • 1995
  • We construct the approximate bootstrap confidence intervals for reliability (R) when the distributions of strength and stress are both normal. Also we propose percentile, bias correct (BC), bias correct acceleration (BCa), and percentile-t intervals for R. We compare with the accuracy of the proposed bootstrap confidence intervals and classical confidence interval based on asymptotic normal distribution through Monte Carlo simulation. Results indicate that the confidence intervals by bootstrap method work better than classical confidence interval. In particular, confidence intervals by BC and BCa method work well for small sample and/or large value of true reliability.

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Bootstrap Method for Row and Column Effects Model

  • Jeong, Hyeong-Chul
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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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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    • 제11권3호
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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
    • 한국시뮬레이션학회논문지
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    • 제1권1호
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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-
    • 한국시뮬레이션학회:학술대회논문집
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    • 한국시뮬레이션학회 1992년도 제2회 정기총회 및 추계학술 발표회 발표논문 초록
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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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체계가용도의 붓스트랩 로버스트 추정

  • 홍연웅
    • 한국정보시스템학회:학술대회논문집
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    • 한국정보시스템학회 1996년도 추계학술발표회 발표논문집
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    • pp.205-210
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    • 1996
  • The bootstrap procedure is suggested as a useful method for point and interval estimation of system availability. Its validity and robustness has been shown in special, but representative case, by various sampling experiments. Alternative to the bootstrap suggest themselves e.g. a variation of the 'F'technique, but remain to be evaluated, as do variations on the bootstrap itself.

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