• 제목/요약/키워드: BOOTSTRAP

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Edgeworth Expansion and Bootstrap Approximation for Survival Function Under Koziol-Green Model

  • Kil Ho;Seong Hwa
    • Communications for Statistical Applications and Methods
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    • 제7권1호
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    • pp.233-244
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    • 2000
  • Confidence intervals for survival function give useful information about the lifetime distribution. In this paper we develop Edgeworkth expansions as approximation to the true and bootstrap distributions of normalized nonparametric maximum likelihood estimator of survival function in the Koziol-Green model and then use these results to show that the bootstrap approximations have second order accuracy.

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꼬리가 두꺼운 분포의 고분위수에 대한 준모수적 붓스트랩 신뢰구간 (Semi-parametric Bootstrap Confidence Intervals for High-Quantiles of Heavy-Tailed Distributions)

  • 김지현
    • Communications for Statistical Applications and Methods
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    • 제18권6호
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    • pp.717-732
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    • 2011
  • 꼬리가 두꺼운 분포의 고분위수에 대한 신뢰구간을 구할 때 적절한 붓스트랩 방법은 무엇인가에 대해 알아보았다. 비모수적 방법과 모수적 방법, 그리고 준모수적 방법의 성능을 모의실험을 통해 비교하였다.

Assessing the Precision of a Jackknife Estimator

  • 박대수
    • Management Science and Financial Engineering
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    • 제9권1호
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    • pp.4-10
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    • 2003
  • We introduce a new estimator of the uncertainty of a jackknife estimate of standard error: the jack-knife-after-jackknife (JAJ). Using Monte Carlo simulation, we assess the accuracy of the JAJ in a variety of settings defined by statistic of interest, data distribution, and sample size. For comparison, we also assess the accuracy of the jackknife-after-bootstrap (JAB) estimate of the uncertainty of a bootstrap standard error. We conclude that the JAJ provides a useful new supplement to Tukey's jackknife, and the combination of jackknife and JAJ provides a useful alternative to the combination of bootstrap and JAB.

Assessing the Precision of a Jackknife Estimator

  • Park, Daesu
    • Management Science and Financial Engineering
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    • 제9권1호
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    • pp.1-10
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    • 2003
  • We introduce a new estimator of the uncertainty of a jackknife estimate of standard error: the jack-knife-after-jackknife (JAJ). Using Monte Carlo simulation, we assess the accuracy of the JAJ in a variety of settings defined by statistic of interest, data distribution, and sample size. For comparison, we also assess the accuracy of the jackknife-after-bootstrap (JAB) estimate of the uncertainty of a bootstrap standard error. We conclude that the JAJ provides a useful new supplement to Tukey's jackknife, and the combination of jackknife and JAJ provides a useful alternative to the combination of bootstrap and JAB.

A New Method of Simulation Output Analysis : Threshold Bootstrap

  • Kim, Yun-Bae-
    • 한국시뮬레이션학회:학술대회논문집
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    • 한국시뮬레이션학회 1993년도 제3회 정기총회 및 추계학술발표회
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    • pp.2-2
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    • 1993
  • Inference for discrete event simulations usually relies on either independent replications or, if each simulation run is expensive, the method of batch means applied to a single replications. We present a new method, threshold bootstrap, which equals or exceeds the performance of independent replications or batch means. The method works by resampling runs of data created when a stationary time series crosses a threshold level, such as the sample mean of series. Computational results show that the threshold bootstrap matches or exceeds the performance of these alternative methods in estimating the standard deviation of the sample mean and producing valid confidence intervals.

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Bootstrap Analysis of ILSTS035 Microsatellite Locus in Hanwoo Chromosome 6

  • Lee, Jea-Young;Lee, Yong-Won;Kim, Mun-Jung
    • Journal of the Korean Data and Information Science Society
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    • 제15권1호
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    • pp.75-81
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    • 2004
  • We selected, in previous research, a major DNA Marker 235bp of ILSTS035 microsatellite locus in progeny test Hanwoo chromosome 6. We apply a major DNA Marker 235bp to perormance valuation Hanwoo chomosome 6. We use bootstrap BCa method and calculate confidence interval. A major DNA Marker 235bp is verified that it does not have environmental effect but affects primely economic trait factor.

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Bootstrap Confidence Intervals for the INAR(p) Process

  • Kim, Hee-Young;Park, You-Sung
    • Communications for Statistical Applications and Methods
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    • 제13권2호
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    • pp.343-358
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    • 2006
  • The distributional properties of forecasts in an integer-valued time series model have not been discovered yet mainly because of the complexity arising from the binomial thinning operator. We propose two bootstrap methods to obtain nonparametric prediction intervals for an integer-valued autoregressive model : one accommodates the variation of estimating parameters and the other does not. Contrary to the results of the continuous ARMA model, we show that the latter is better than the former in forecasting the future values of the integer-valued autoregressive model.

Major DNA Marker Mining of Hanwoo Chromosome 6 by Bootstrap Method

  • Lee, Jea-Young;Lee, Yong-Won
    • Communications for Statistical Applications and Methods
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    • 제11권3호
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    • pp.657-668
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    • 2004
  • Permutation test has been applied for the QTL(quantitative trait loci) analysis and we selected a major locus. K -means clustering analysis, for the major DNA Marker mining of ILSTS035 microsatellite loci in Hanwoo chromosome 6, has been described. Finally, bootstrap testing method has been adapted to calculate confidence intervals and for finding major DNA Markers.

VQ 방식의 화자인식 시스템 성능 향상을 위한 부쓰트랩 방식 적용 (The bootstrap VQ model for automatic speaker recognition system)

  • 경연정;이진익;이황수
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 2000년도 하계학술발표대회 논문집 제19권 1호
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    • pp.39-42
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    • 2000
  • VQ 모델로 구성된 화자인식 시스템의 성능 향상을 위해 Bootstrap 방식을 적용하였다. Bootstrap 및 aggregating방식은 unstable한 모델에서 그 성능이 유효하므로 이의 적용을 위해 먼저 VQ 모델의 bias와 variance를 계산하여 unstable함을 보였다. 화자인식 실험은 TIMIT Database를 사용하여 수행하였고 실험결과 높은 인식율 향상을 확인하였다. 또한 적은 훈련 데이터 환경에서도 좋은 인식율을 갖는 것으로 나타났다.

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희귀모형의 선형성에 대한 커널붓스트랩검정 (A Bootstrap Test for Linear Relationship by Kernel Smoothing)

  • 백장선;김민수
    • Journal of the Korean Data and Information Science Society
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    • 제9권2호
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    • pp.95-103
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    • 1998
  • 회귀모형의 선형성을 검정하는 방법으로서 Azzalini와 Bowman은 회귀모형의 오차항이 정규분포를 따른다는 가정하에서 커널회귀추정량을 이용한 유사우도비 검정이라는 비모수적 방법을 제안하였다. 붓스트랩(bootstrap)기법을 도입하여 그들의 검정방법을 변형한 커널붓스트랩검정이라는 새로운 검정법을 제시하고 모의실험을 통해 검정력을 살펴보았다. 제안된 방법은 오차항의 분포가 정규분포가 아닌 경우에도 적용이 가능하였다.

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