• 제목/요약/키워드: Parametric bootstrap

검색결과 68건 처리시간 0.017초

$\bar{x}$ 관리도의 표준관리한계와 부트스트랩 백분률 관리한계의 수행도 비교평가 (Comparison and Evaluation of Performance for Standard Control Limits and Bootstrap Percentile Control Limits in $\bar{x}$ Control Chart)

  • 송서일;이만웅
    • 산업경영시스템학회지
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    • 제22권52호
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    • pp.347-354
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    • 1999
  • Statistical Process Control(SPC) which uses control charts is widely used to inspect and improve manufacturing process as a effective method. A parametric method is the most common in statistical process control. Shewhart chart was made under the assumption that measurements are independent and normal distribution. In practice, this assumption is often excluded, for example, in case of (equation omitted) chart, when the subgroup sample is small or correlation, it happens that measured data have bias or rejection of the normality test. A bootstrap method can be used in such a situation, which is calculated by resampling procedure without pre-distribution assumption. In this study, applying bootstrap percentile method to (equation omitted) chart, it is compared and evaluated standard process control limit with bootstrap percentile control limit. Also, under the normal and non-normal distributions, where parameter is 0.5, using computer simulation, it is compared standard parametric with bootstrap method which is used to decide process control limits in process quality.

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Testing the Goodness of Fit of a Parametric Model via Smoothing Parameter Estimate

  • Kim, Choongrak
    • Journal of the Korean Statistical Society
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    • 제30권4호
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    • pp.645-660
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    • 2001
  • In this paper we propose a goodness-of-fit test statistic for testing the (null) parametric model versus the (alternative) nonparametric model. Most of existing nonparametric test statistics are based on the residuals which are obtained by regressing the data to a parametric model. Our test is based on the bootstrap estimator of the probability that the smoothing parameter estimator is infinite when fitting residuals to cubic smoothing spline. Power performance of this test is investigated and is compared with many other tests. Illustrative examples based on real data sets are given.

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꼬리가 두꺼운 분포의 고분위수에 대한 신뢰구간 (Confidence Intervals for High Quantiles of Heavy-Tailed Distributions)

  • 김지현
    • 응용통계연구
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    • 제27권3호
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    • pp.461-473
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    • 2014
  • 꼬리가 두꺼운 분포의 고분위수에 대한 신뢰구간을 연구하였다. 통계량의 극한 분포에 근거한 점근적 방법과 붓스트랩 방법을 같이 고려하였다. 이 두 방법에 모수적, 비모수적, 준모수적 기법을 각각 적용할 수 있는데, 전체 11가지 신뢰구간의 성능을 실제신뢰수준과 길이로 비교하였다. 모의실험 결과 준모수적이면서 점근적인 신뢰구간과 축량을 이용하는 준모수적 붓스트랩 신뢰구간이 실제신뢰수준의 기준에서 안정된 성능을 보인다는 것을 알 수 있었다.

Bootstrap tack of Fit Test based on the Linear Smoothers

  • Kim, Dae-Hak
    • Journal of the Korean Data and Information Science Society
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    • 제9권2호
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    • pp.357-363
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    • 1998
  • In this paper we propose a nonparametric lack of fit test based on the bootstrap method for testing the null parametric linear model by using linear smoothers. Most of existing nonparametric test statistics are based on the residuals. Our test is based on the centered bootstrap residuals. Power performance of proposed bootstrap lack of fit test is investigated via Monte carlo simulation.

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Bootstrap and Delete-d Jackknife Confidence Intervals for Parameters of an Exponential Distribution

  • Kang, Suk-Bok;Cho, Young-Suk
    • Journal of the Korean Data and Information Science Society
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    • 제8권1호
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    • pp.59-70
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    • 1997
  • We introduce several estimators of the location and the scale parameters of the two-parameter exponential distribution, and then compare these estimators by the mean square error (MSE). Using the parametric bootstrap estimators and the delete-d jackknife, we obtain the bootstrap and the delete-d jackknife confidence intervals for the location and the scale parameters and compare the bootstrap confidence intervals with the delete-d jackknife confidence intervals by length and coverage probability through Monte Carlo method.

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Bootstrap methods for long-memory processes: a review

  • Kim, Young Min;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • 제24권1호
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    • pp.1-13
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    • 2017
  • This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

Double Bootstrap Confidence Cones for Sphericla Data based on Prepivoting

  • Shin, Yang-Kyu
    • Journal of the Korean Statistical Society
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    • 제24권1호
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    • pp.183-195
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    • 1995
  • For a distribution on the unit sphere, the set of eigenvectors of the second moment matrix is a conventional measure of orientation. Asymptotic confidence cones for eigenvector under the parametric assumptions for the underlying distributions and nonparametric confidence cones for eigenvector based on bootstrapping were proposed. In this paper, to reduce the level error of confidence cones for eigenvector, double bootstrap confidence cones based on prepivoting are considered, and the consistency of this method is discussed. We compare the perfomances of double bootstrap method with the others by Monte Carlo simulations.

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구형자료(球型資料)에 대(對)한 부트스트랩 신뢰원추체(信賴圓錐體) (Bootstrap Confidence Cones for Spherical Data)

  • 신양규
    • Journal of the Korean Data and Information Science Society
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    • 제3권1호
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    • pp.33-46
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    • 1992
  • The set of eigenvectors of the second moment matrix and the mean vector are the measures of orientation for a distribution supported on the unit sphere. Bootstrap confidence cone for the eigenvector is constructed and the consistency of this method is discussed. The performance of our bootstrap cone for the eigenvector is compared with that of the asymptotic confidence cones for two measures under the parametric assumptions for the underlying distributions and that of the bootstrap cone for the mean vector by Monte Carlo simulation.

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ENTROPY-BASED GOODNESS OF FIT TEST FOR A COMPOSITE HYPOTHESIS

  • Lee, Sangyeol
    • 대한수학회보
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    • 제53권2호
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    • pp.351-363
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    • 2016
  • In this paper, we consider the entropy-based goodness of fit test (Vasicek's test) for a composite hypothesis. The test measures the discrepancy between the nonparametric entropy estimate and the parametric entropy estimate obtained from an assumed parametric family of distributions. It is shown that the proposed test is asymptotically normal under regularity conditions, but is affected by parameter estimates. As a remedy, a bootstrap version of Vasicek's test is proposed. Simulation results are provided for illustration.

Bootstrap 기법을 이용한 BOD 평균 농도 및 신뢰구간 분석 (Analysis of BOD Mean Concentration and Confidence Interval using Bootstrap Technique)

  • 김경섭
    • 한국물환경학회지
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    • 제26권2호
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    • pp.297-302
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    • 2010
  • It is very important to know mean and confidence interval of water-quality constituents such as BOD for water-quality control and management of rivers and reservoirs effectively. The mean and confidence interval of BOD at Anseong2 and Hwangguji3 sampling stations which are located at the border of local governments in Anseong Stream were estimated and analyzed in this paper using Bootstrap technique which is one of non-parametric statistics. The results of Bootstrap were compared with arithmetic mean, geometric mean, Biweight method mean as a point estimator and distribution mean came from the appropriate probability distribution of Log-normal. In Bootstrap technique 12 data set was randomly selected in each year and 1000 samples was produced to get parameter of population. Visual Basic for Applications (VBA) of Microsoft Excel was utilized in Bootstrap. It was revealed that the Bootstrap technique can be used to explain more rigorously and robustly the achievement or violation of BOD target concentration in Total Maximum Daily Load (TMDL).