• Communications for Statistical Applications and Methods
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• v.7 no.1
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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.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.717-732
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• 2011

We consider bootstrap confidence intervals for high quantiles of heavy-tailed distribution. A semi-parametric method is compared with the non-parametric and the parametric method through simulation study.

• Management Science and Financial Engineering
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• v.9 no.1
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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.

• Management Science and Financial Engineering
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• v.9 no.1
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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.

• Proceedings of the Korea Society for Simulation Conference
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• 1993.10a
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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.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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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.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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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.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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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.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.39-42
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• 2000

A bootstrap and aggregating (bagging) vector quantization (VQ) classifier is proposed for speaker recognition. This method obtains multiple training data sets by resampling the original training data set, and then integrates the corresponding multiple classifiers into a single classifier. Experiments involving a closed set, text-independent and speaker identification system are carried out using the TIMIT database. The proposed bagging VQ classifier shows considerably improved performance over the conventional VQ classifier.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.95-103
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• 1998

Azzalini and Bowman proposed the pseudo-likelihood ratio test for checking the linear relationship using kernel regression estimator when the error of the regression model follows the normal distribution. We modify their method with the bootstrap technique to construct a new test, and examine the power of our test through simulation. Our method can be applied to the case where the distribution of the error is not normal.