• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.844-851
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• 2009

Since 1990s, the European railway sector has undergone both a vertical separation and a vertical integration. Recently Simar and Wilson (2008) provides a bootstrap test procedure for testing whether two groups' mean efficiencies are equivalent. The purpose of this paper is to ascertain the relationship between vertical separation and operational efficiency of railway industry using the Simar and Wilson's bootstrap test procedure not used in previous studies with a data set of 20 European countries from 1998 to 2005. From the value of test statistic it seems that the mean operational efficiencies of vertically separated railway industry were higher than those of vertically integrated railway industry. However the p-value indicates that the differences of mean operational efficiencies are not significat at any meaningful level.

• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.235-245
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• 1996

In this paper, we studied about several methods of testing hypothesis of correlation, specially Approximate method, Empirical method and Bootstrap method. The Approximate method is based on the Fisher's Z-transformation and the Empirical and Bootstrap methods approximate the distribution of the sample correlation coefficient by Monte Carlo simulation and Bootstrap technique, respectively. In order to compare how good these tests are, we computed powers under various alternatives. Consequently, we see that the Approximate test performs very well even if in small sample and all tests have almost the same power in large sample.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.185-188
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• 2008

This paper introduces the Bootstrap method for statistical analysis of noise and vibration spectrum in aeronautic and space fields. Generally, all components of a launch vehicle and its payloads are subjected to high intensive noise and vibration environment during the lift-off phase and the ascent phase through Mach =1 and Max Q. In order to verify their survivabilities against these severe vibroacoustic environments during qualification tests and acceptance tests, it is most important to estimate the proper upper limits of the environmental condition. Although NASA has typically utilized the Normal Tolerance Limit method in deriving these levels, the reference[1] says that the Bootstrap can be also an alternative method to estimate the maximum expected environments. In this paper, a general procedure of the Bootstrap method is summarized, and it is applied to analyze acceleration power spectral density functions, which were measured during acoustic test on the upper stage of KSLV-I.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.475-487
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• 2015

This study measures the managerial efficiency of Korea's 14 public enterprises using bootstrap DEA in 2013. In addition, it examines the factors that affect on the bootstrap bias-corrected efficiency using truncated regression analysis. The results and implications of this study are as follows. First, using bootstrap DEA model analysis, the results showed that the mean technical efficiency was 0.3182, the mean pure technical efficiency was 0.4994 and the mean scale efficiency was 0.6585. The main cause of technical inefficiency was due to pure technical inefficiency. Second, rank test between technical efficiency of general DEA model and bootstrap DEA model was no significant difference under CRS and VRS assumption. Third, the main cause of the inefficiency in 11 DMUs among 14 DMUs were mainly due to the pure technology and three DMUs were because of the scale efficiency. Finally, in the truncated regression analysis, cost of labor, profit, sales, return of equity, and the number of employees appeared as factors affecting the scale efficiency at the 10% significance level.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.325-329
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• 2003

한우 6번 염색체 유전자 지도에서 QTL (quantitative trait loci) 분석을 실시하여 선별된Locus 값을 순열검정(Permutation Test)을 이용하여 유의성 검정을 실시하였다. 한편, 우수경제형질 DNA marker들을 K-평균 군집법을 실시 파악하였다. 이들 QTL과 K-평균법에 의해 한우의 염색체 6번 ILSTS035의 우수 DNA marker 235번을 선별하였다. 선별된 DNA Marker 235번을 출품우에 적용하여 Bootstrap 방법을 이용하여 신뢰구간을 구하여 검정하였다.

• The Korean Journal of Physiology and Pharmacology
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• v.13 no.5
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• pp.367-371
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• 2009

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled data sets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.

• Proceedings of the Korean Association for Survey Research Conference
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• 2006.06a
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• pp.131-159
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• 2006

This paper consider multinomial group testing which is concerned with classification each of N given units into one of k disjoint categories. In this paper, we propose exact Bayesian, approximate Bayesian, bootstrap methods for estimating individual category proportions using the multinomial group testing model proposed by Bar-Lev et al (2005). By the comparison of Mcan Squre Error (MSE), it is shown that the exact Bayesian method has a bettor efficiency and consistency than maximum likelihood method. We suggest an approximate Bayesian approach using Markov Chain Monte Carlo (MCMC) for posterior computation. We derive exact credible intervals based on the exact Bayesian estimators and present confidence intervals using the bootstrap and MCMC. These intervals arc shown to often have better coverage properties and similar mean lengths to maximum likelihood method already available. Furthermore the proposed models are illustrated using data from a HIV blooding test study throughout California, 2000.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.355-366
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• 2002

Nonparametric statistical inference for the parameter of logit model were examined. Usually nonparametric approach is milder than parametric approach based on normal theory assumption. We compared the two nonparametric methods for legit model, the bootstrap and random permutation in the sense of coverage probability. Monte Carlo simulation is conducted for small sample cases. Empirical power of hypothesis test and coverage probability for confidence interval estimation were presented for simple and multiple legit model respectively. An example were also introduced.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.753-761
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• 2019

A test procedure based on a Kendall's τ statistic is proposed for the association of bivariate interval censored data. In particular, a leverage bootstrap technique is applied to replace unknown failure times and a classical adjustment method is applied for treating tied observations. The suggested method shows desirable results in simulation studies. An AIDS dataset is analyzed with the suggested method.

• Journal of Korean Society for Quality Management
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• v.42 no.2
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• pp.209-219
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• 2014

Purpose: The purpose of this study is to develop the statistical test for process capability index $C_p$ based on mixture normal process. Methods: This study uses Bootstrap method to calculate the approximate P-value for various simulation conditions under mixture normal process. Results: This study indicates that our proposed method is effective way to test for process capability index $C_p$ based on mixture normal process. Conclusion: This study finds out that statistical test for process capability index $C_p$ based on mixture normal process is useful for real application.