• Journal of the Korean Data and Information Science Society
• /
• 제8권1호
• /
• pp.41-48
• /
• 1997

We construct the empirical Bayes(EB) confidence intervals that attain a specified level of EB coverage for the unknown scale parameter in the Weibull distribution with the known shape parameter under the type II censored data. Our general approach is to use an EB bootstrap samples introduced by Larid and Louis(1987). Also, we compare the coverage probability and the expected interval length for these bootstrap intervals with those of the naive intervals through Monte Carlo simulation.

• Journal of the Korean Data and Information Science Society
• /
• 제24권1호
• /
• pp.189-200
• /
• 2013

In this paper, it will be assumed that there are two distinct populations which are multivariate normal with equal covariance matrix. We also assume that the two populations are equally likely and the costs of misclassification are equal. The classification rule depends on the situation whether the training samples include missing values or not. We consider the conditional bootstrap confidence intervals for classification error rate when a block of observation is missing.

• 응용통계연구
• /
• 제16권2호
• /
• pp.377-393
• /
• 2003

본 논문에서는 두 모비율의 차에 대한 기존의 신뢰구간들을 소개하고 붓스트랩 신뢰구간도 제안하였다 또한 모비율의 차에 대한 신뢰구간이 가지는 성질로서 근사신뢰구간의 하향추정의 문제와 정확신뢰구간의 상향추정의 문제점들을 확인하였고 평균포함 확률, 구간기대폭 그리고 왜도성 측면에서 종합적인 비교를 하였다. 특히 모수에 대한 사전분포를 가정하여 여러 신뢰구간들이 지니는 특징도 살펴보았다 기존의 신뢰구간들과 제안된 붓스트랩 신뢰구간은 소표본의 모의실험을 통하여 실제 포함확률의 평균을 기준으로 비교되었고 이항분포에서와 같이 정확신뢰구간이 지니는 보수성을 확인할 수 있었다. 신뢰구간의 평균포함확률의 등고선 그림도 소개하였다.

• Communications for Statistical Applications and Methods
• /
• 제13권2호
• /
• pp.343-358
• /
• 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.

• Journal of the Korean Statistical Society
• /
• 제28권3호
• /
• pp.359-370
• /
• 1999

We considered a change-point hazard rate model generalizing constant hazard rate model. This type of model is very popular in the sense that the Weibull and exponential distributions formulating survival time data are the special cases of it. Maximum likelihood estimation and the asymptotic properties such as the consistency and its limiting distribution of the change-point estimator were discussed. A parametric bootstrap method for finding confidence intervals of the unknown change-point was also suggested and the proposed method is explained through a practical example.

• 응용통계연구
• /
• 제11권1호
• /
• pp.53-64
• /
• 1998

수리 가능한 시스템에 대한 고장시간을 표현하는 여러가지 형태의 통계적 모형이 최근 엔지니어들과 신뢰성분야 학자들의 많은 관심을 끌고 있다. 본 논문에서는 수리가능한 시스템의 신뢰성 증가를 나타내는데 유용하게 적용되는 power law process를 고려하고 특히 정시중단자료(time truncated data)인 경우 고장간격에 대한 신뢰구간을 붓스트랩 기법을 이용하여 구하고 이것을 Crow(1982)가 구한 기존의 신뢰구간과 비교 분석하였다.

• 한국수산과학회지
• /
• 제41권2호
• /
• pp.107-112
• /
• 2008

To evaluate uncertainty and risk in biological reference points, we applied a bootstrapping method and a Bayesian procedure to estimate the related confidence intervals. Here we provide an example of the maximum sustainable yield (MSY) of turban shell, Batillus cornutus, estimated by the Schaefer and Fox models. Fitting the time series of catch and effort from 1968 to 2006 showed that the Fox model performs better than the Schaefer model. The estimated MSY and its bootstrap percentile confidence interval (CI) at ${\alpha}=0.05$ were 1,680 (1,420-1,950) tons for the Fox model and 2,170 (1,860-2,500) tons for the Schaefer model. The CIs estimated by the Bayesian approach gave similar ranges: 1,710 (1,450-2,000) tons for the Fox model and 2,230 (1,760-2,930) tons for the Schaefer model. Because uncertainty in effort and catch data is believed to be greater for earlier years, we evaluated the influence of sequentially excluding old data points by varying the first year of the time series from 1968 to 1992 to run 'backward' bootstrap resampling. The results showed that the means and upper 2.5% confidence limit (CL) of MSY varied greatly depending on the first year chosen whereas the lower 2.5% CL was robust against the arbitrary selection of data, especially for the Schaefer model. We demonstrated that the bootstrap and Bayesian approach could be useful in precautionary fisheries management, and we advise that the lower 2.5% CL derived by the Fox model is robust and a better biological reference point for the turban shells of Jeju Island.

• 한국품질경영학회:학술대회논문집
• /
• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
• /
• pp.174-179
• /
• 1998

This research explores the application of the bootstrap methods to the construction of control limits for the x charts and the EWMA charts based on single observations with stationary autoregressive processes. The subsample means-based control chars in the presence autocorrelation are also considered. We use a technique for inferring confidence intervals using bootstrap, the percentile method. Simulation studies are conducted to compare the performance of the bootstrap method and that of standard method for constructing control charts under several conditions.

• Communications for Statistical Applications and Methods
• /
• 제11권3호
• /
• pp.447-454
• /
• 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.

• 한국시뮬레이션학회논문지
• /
• 제1권1호
• /
• pp.31-36
• /
• 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.