• Title/Summary/Keyword: 붓스트랩의 일치성

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붓스트랩 표준편차 추정량으로 표준화한 U-통계량을 이용한 비모수적 검정법

  • 이기훈
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.221-226
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    • 1995
  • 본 연구는 붓스트랩에 의한 U-통계량의 분산추정방법을 제안하고, 추정량의 일치성을 증명하였다. 결과적으로 붓스트랩 추정량으로 표준화한 U-통계량의 값이 표준정규분포에 근사함을 보였다. 또한 실제적인 비모수검정에서 이를 응용하여 검정력과 특성을 연구하였다.

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On Statistical Inference of Stratified Population Mean with Bootstrap (층화모집단 평균에 대한 붓스트랩 추론)

  • Heo, Tae-Young;Lee, Doo-Ri;Cho, Joong-Jae
    • Communications for Statistical Applications and Methods
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    • v.19 no.3
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    • pp.405-414
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    • 2012
  • In a stratified sample, the sampling frame is divided into non-overlapping groups or strata (e.g. geographical areas, age-groups, and genders). A sample is taken from each stratum, if this sample is a simple random sample it is referred to as stratified random sampling. In this paper, we study the bootstrap inference (including confidence interval) and test for a stratified population mean. We also introduce the bootstrap consistency based on limiting distribution related to the plug-in estimator of the population mean. We suggest three bootstrap confidence intervals such as standard bootstrap method, percentile bootstrap method and studentized bootstrap method. We also suggest a bootstrap test method computing the $ASL_{boot}$(Achieved Significance Level). The results of estimation are verified using simulation.

Bootstrap confidence interval for survival function in the Koziol-Green model (KOZIOL-GREEN 모형에서 생존함수에 대한 붓스트랩 구간추정)

  • 조길호;정성화;최달우;최현숙
    • The Korean Journal of Applied Statistics
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    • v.11 no.1
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    • pp.151-161
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    • 1998
  • We study the bootstrap interval estimation for survival function in the Koziol-Green model. We construct the approximate bootstrap confidence intervals for survival function and prove the strong consistency for the bootstrap estimator of survival function. Finally we show that the approximate bootstrap confidence intervals are better in terms of coverage probability than confidence intervals based on asymptotic normal distribution and transformations of survival function via Monte Carlo simulation study.

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A concordance test for bivariate interval censored data using a leverage bootstrap (지렛대 붓스트랩을 이용한 이변량 구간 중도 절단 자료의 일치성 검정)

  • Kim, Yang-Jin
    • 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.

The Application of Bootstrap Methods for Correspondence Analysis (대응분석에 있어서 붓스트랩 방법의 활용에 대한 고찰)

  • 강창완;김대학;전명식
    • The Korean Journal of Applied Statistics
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    • v.14 no.2
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    • pp.401-413
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    • 2001
  • 이차원 분할자료에 대해서 행과 열의 관계를 저차원상에 시각적으로 표현하는 탐색적대응분석에 대하여 붓스트랩방법의 사용가능성을 살펴보았다. 기존의 탐색적 면만이 강조되어 왔던 대응분석에서 좌표점의 변이와 좌표점간의 거리에 대한 통계적 추론을 붓스트랩방법으로 해결할 수 있음을 보이고 또한 좌표축의 설명력에 대하여 붓스트랩신뢰구간의 포함확률의 일치성을 모의실험을 통해 제시하였다.

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Nonparametric estimation of hazard rates change-point (위험률의 변화점에 대한 비모수적 추정)

  • 정광모
    • The Korean Journal of Applied Statistics
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    • v.11 no.1
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    • pp.163-175
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    • 1998
  • The change of hazard rates at some unknown time point has been the interest of many statisticians. But it was restricted to the constant hazard rates which correspond to the exponential distribution. In this paper we generalize the change-point model in which any specific functional forms of hazard rates are net assumed. The assumed model includes various types of changes before and after the unknown time point. The Nelson estimator of cumulative hazard function is introduced. We estimate the change-point maximizing slope changes of Nelson estimator. Consistency and asymptotic distribution of bootstrap estimator are obtained using the martingale theory. Through a Monte Carlo study we check the performance of the proposed method. We also explain the proposed method using the Stanford Heart Transplant Data set.

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Test of Hypothesis in Assessing Process Capability Index Cpmk (공정능력지수 Cpmk를 평가함에서의 바람직한 가설검정)

  • Cho, Joong-Jae;Yu, Hye-Kyung;Hana, Jung-Su
    • Communications for Statistical Applications and Methods
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    • v.17 no.3
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    • pp.459-471
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    • 2010
  • Higher quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. Usually, the quality level is measured by process capability indices. The index is used to determine whether a production process is capable of producing items within a specified tolerance. The third generation index $C_{pmk}$ is more powerful than two useful indices $C_p$ and $C_{pk}$. which have been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. In this paper, we consider better testing procedure on assessing process capability index $C_{pmk}$ for practitioners to use in determining whether a given process is capable. It is easy to use the proposed method for assessing process capability index $C_{pmk}$. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on our proposed method is illustrated.