• Communications for Statistical Applications and Methods
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• 제15권5호
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• pp.643-653
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• 2008

Application of the bootstrap to problems in multistage inference procedures are discussed in normal and other related models. After a general introduction to these procedures, here we explore in multistage fixed precision inference in models. We present numerical comparisons of these procedures based on bootstrap critical points for small and moderate sample sizes obtained via extensive sets of simulated experiments. It is expected that the procedure based on bootstrap leads to better results.

• Journal of the Korean Statistical Society
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• 제30권1호
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• pp.1-20
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• 2001

We present how bootstrap methods can be used to conduct inference on the rates of Poisson distributions when only the grouped data are available. A theoretical justification for the validity of bootstrap is given with an illustration of proposed method using a data set obtained fro ma pathology laboratory test. Traditional asymptotic methods are compared with bootstrap methods in computing the estimated standard errors and achieved significance levels for one sample and two sample tests. Bootstrap methods are shown to possess a nice property that he small sample distribution of the relevant statistics can be readily obtained from the bootstrap copies.

• 품질경영학회지
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• 제32권4호
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• pp.229-241
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• 2004

Process capability index is used to determine whether a production process is capable of producing items within a specified tolerance. The index $C_{pmk}$ is the third generation process capability index. This index is more powerful than two useful indices $C_p$ and $C_{pk}$. Whether a process distribution is clearly normal or nonnormal, there may be some questions as to which any process index is valid or should even be calculated. As far as we know, yet there is no result for statistical inference with process capability index $C_{pmk}$. However, asymptotic method and bootstrap could be studied for good statistical inference. In this paper, we propose various bootstrap confidence limits for our process capability Index $C_{pmk}$. First, we derive bootstrap asymptotic distribution of plug-in estimator $C_{pmk}$ of our capability index $C_{pmk}$. And then we construct various bootstrap confidence limits of our capability index $C_{pmk}$ for more useful process capability analysis.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 춘계 학술대회 논문집
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• pp.169-169
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• 2001

With the aid of fast computing power, resampling techniques are being introduced for simulation output analysis (SOA). Autocorrelation among the output from discrete-event simulation prohibit the direct application of resampling schemes (Threshold bootstrap, Binary bootstrap, Stationary bootstrap, etc) extend its usage to time-series data such as simulation output. We present a new method for inference from a regenerative process, regenerative bootstrap, that equals or exceeds the performance of classical regenerative method and approximation regeneration techniques. Regenerative bootstrap saves computation time and overcomes the problem of scarce regeneration cycles. Computational results are provided using M/M/1 model.

• Communications for Statistical Applications and Methods
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• 제19권3호
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• pp.405-414
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• 2012

층화확률추출은 모집단을 어떤 층화기준에 의해 여러 층으로 분할한 다음 각 층으로부터 독립적으로 표본을 임의추출하는 방법으로 여러 가지 장점을 가지고 있어 실제 조사에서 많이 활용되고 있다. 본 연구에서는 대규모 표본조사에서 많이 사용하고 있는 층화확률추출을 사용하여 추출된 표본을 통해 모평균에 대한 붓스트랩 추정량과 신뢰구간 및 가설검정 등 통계적 추론에 대하여 연구하였다. 층화모집단에서의 모평균의 추정량과 관련된 극한 분포이론들을 기초로 붓스트랩 일치성을 근거로 층화 모평균에 대해 표준 붓스트랩 방법, 백분위수 붓스트랩 방법, 스튜던트화 붓스트랩 방법을 활용한 신뢰구간과 붓스트랩 가설검정 방법을 제안하였으며, 모의실험을 통해 신뢰구간 추정 방법들의 유효성을 확인하였다.

• Journal of the Korean Statistical Society
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• 제36권2호
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• pp.257-274
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• 2007

This paper considers the tests for the presence of smooth transition non-linearity in the partially nonstationary vector autoregressive model. The transition parameters cannot be identified under the null hypothesis of linearity, and therefore this paper develops the tests for smooth transition nonlinearity, the associated asymptotic theory and the bootstrap inference. The Monte Carlo simulation evidence shows that the bootstrap inference generates moderate size and power performances.

• Journal of the Korean Statistical Society
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• 제22권2호
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• pp.159-169
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• 1993

In this article, we consider two sample problem with randomly right censored data. We propse two-sample confidence intervals for the difference in medians or any quantiles, based on bootstrap. The bootstrap version of two-sample confidence intervals proposed in this article is simple to apply and do not need the assumption of the shift model, so that for the non-shift model, the density estimation is not necessary, which is an attractive feature in small to moderate sized sample case.

• 응용통계연구
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• 제15권2호
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• pp.355-366
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• 2002

범주형 자료의 구조파악에 주로 이용되는 로짓모형에서 비모수적 방법을 이용한 모수의 신뢰구간추정과 가설검정 등의 통계적 추론에 대하여 살펴보았다. 모수에 대한 통계적 추론에서 정규분포에 근거한 모수적 방법(Wald 방법)보다는 붓스트랩 방법이나 임의순열을 활용한 비모수적 방법이 많이 활용되고 있다. 본 연구에서는 로짓모형의 모수에 대한 비모수적 추론방법으로 붓스트랩(bootstrap)과 임의순열(random permutation)의 두 방법을 고려하고 모의실험을 통하여 가설검정의 검정력과 신뢰구간추정의 포함확률을 비교하였고 사례분석을 다루었다.

• Journal of the Korean Statistical Society
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• 제24권1호
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• pp.197-218
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• 1995

We first consider the random censorship model of survival analysis. Efron (1981) introduced two equivalent bootstrap methods for censored data. We propose a new bootstrap scheme, called Method 3, that acts conditionally on the censoring pattern when making inference about aspects of the unknown life-time distribution F. This article contains (a) a motivation for this refined bootstrap scheme ; (b) a proof that the bootstrapped Kaplan-Meier estimatro fo F formed by Method 3 has the same limiting distribution as the one by Efron's approach ; (c) description of and report on simulation studies assessing the small-sample performance of the Method 3 ; (d) an illustration on some Danish data. We also consider the model in which the survival times are censered by death times due to other caused and also by known fixed constants, and propose an appropriate bootstrap method for that model. This bootstrap method is a readily modified version of the Method 3.

• Journal of applied mathematics & informatics
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• 제7권2호
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• pp.467-482
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• 2000

Testing equality of two and k distributions has long been an interesting issue in statistical inference. To overcome the sparseness of data points in high-dimensional space and deal with the general cases, we suggest several projection pursuit type statistics. Some results on the limiting distributions of the statistics are obtained, some properties of Bootstrap approximation are investigated. Furthermore, for computational reasons an approximation for the statistics the based on Number theoretic method is applied. Several simulation experiments are performed.