• 제목/요약/키워드: Bootstrap interval estimation

검색결과 31건 처리시간 0.028초

On the Performance of Iterated Wild Bootstrap Interval Estimation of the Mean Response

  • Kim, Woo-Chul;Ko, Duk-Hyun
    • Journal of the Korean Statistical Society
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    • 제24권2호
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    • pp.551-562
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    • 1995
  • We consider the iterated bootstrap method in regression model with heterogeneous error variances. The iterated wild bootstrap confidence intervla of the mean response is considered. It is shown that the iterated wild bootstrap confidence interval has coverage error of order $n^{-1}$ wheresa percentile method interval has an error of order $n^{-1/2}$. The simulation results reveal that the iterated bootstrap method calibrates the coverage error of percentile method interval successfully even for the small sample size.

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Bootstrap Confidence Intervals for the Difference of Quantiles of Right Censored Data

  • Na, Jong-Hwa;Park, Hyo-Il;Jang, Young-Mi
    • Communications for Statistical Applications and Methods
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    • 제11권3호
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    • pp.447-454
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    • 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.

Prediction Intervals for LS-SVM Regression using the Bootstrap

  • Shim, Joo-Yong;Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • 제14권2호
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    • pp.337-343
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    • 2003
  • In this paper we present the prediction interval estimation method using bootstrap method for least squares support vector machine(LS-SVM) regression, which allows us to perform even nonlinear regression by constructing a linear regression function in a high dimensional feature space. The bootstrap method is applied to generate the bootstrap sample for estimation of the covariance of the regression parameters consisting of the optimal bias and Lagrange multipliers. Experimental results are then presented which indicate the performance of this algorithm.

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최소카이제곱추정과 붓스트랩 (Minimum Chi-square estimation and the bootstrap)

  • 정한영;이기원;구자용
    • 응용통계연구
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    • 제7권2호
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    • pp.269-277
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    • 1994
  • 최소카이제곱추정에 의하여 구한 추정량의 표본분포를 붓스트랩으로 근사시켰을 때에도 정규근사와 최소한 동등함을 설명하고, 이 이론을 자궁경부암 조직에서 검출되는 란게르한스 세포의 출현률 추정에 이용하였다. 란게르한스 세포의 출현횟수를 포지티브 포아송 모형에 적합시켰으며, 추정된 출현률의 표준오차는 대표본 근사 및 붓스트랩을 이용하여 계산하였다. 두 방법 모두 비슷한 결과를 제공하였다.

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체계가용도의 붓스트랩 로버스트 추정

  • 홍연웅
    • 한국정보시스템학회:학술대회논문집
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    • 한국정보시스템학회 1996년도 추계학술발표회 발표논문집
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    • pp.205-210
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    • 1996
  • The bootstrap procedure is suggested as a useful method for point and interval estimation of system availability. Its validity and robustness has been shown in special, but representative case, by various sampling experiments. Alternative to the bootstrap suggest themselves e.g. a variation of the 'F'technique, but remain to be evaluated, as do variations on the bootstrap itself.

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체계가용도의 붓스트랩 로버스트 추정

  • 홍연웅
    • 한국산업정보학회:학술대회논문집
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    • 한국산업정보학회 1996년도 추계 학술 발표회 발표논문집
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    • pp.205-210
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    • 1996
  • The bootstrap procedure is suggested as a useful method for point and interval estimation of system availability . Its validity and robustness has been shown in special , but representative case, by various sampling experiments. Alternative to the bootstrap suggest themselves (e.g. a variation of the 'F' technique, but remain to be evaluated, as do variations on the bootstrap itself.

On Employing Nonparametric Bootstrap Technique in Oscillometric Blood Pressure Measurement for Confidence Interval Estimation

  • Lee, Yong-Kook;Lee, Im-Bong;Chang, Joon-Hyuk;Lee, Soo-Jeong
    • 한국멀티미디어학회논문지
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    • 제17권2호
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    • pp.200-207
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    • 2014
  • Blood pressure (BP) is an important vital signal for determining the health of an individual subject. Although estimation of mean arterial blood pressure is possible using oscillometric blood pressure techniques, there are no established techniques in the literature for obtaining confidence interval (CI) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates obtained from such BP measurements. This paper proposes a nonparametric bootstrap technique to obtain CI with a small number of the BP measurements. The proposed algorithm uses pseudo measurements employing nonparametric bootstrap technique to derive the pseudo maximum amplitudes (PMA) and the pseudo envelopes (PE). The SBP and DBP are then derived using the new relationships between PMA and PE and the CIs for such estimates. Application of the proposed method on an experimental dataset of 85 patients with five sets of measurements for each patient has yielded a smaller Cl than the conventional student t-method.

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

  • 조길호;정성화;최달우;최현숙
    • 응용통계연구
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    • 제11권1호
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    • pp.151-161
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    • 1998
  • 본 논문에서는 Koziol-Green 모형에서 생존함수에 대한 신뢰구간을 붓스트랩 방법을 이용하여 제안하고, 생존함수에 대한 붓스트랩 추정량의 일치성을 밝힌다. 또한 제안된 붓스트랩 신뢰구간들을 기존의 근사적 정규분포를 이용한 신뢰구간과 생존함수에 변수변환을 고려하여 구성한 신뢰구간들과 모의실험을 통하여 비교한 결과 제안된 붓스트랩 신뢰구간이 기존의 방법보다 포함확률 측면에서 더 좋은 결과를 보였고 중도절단율에 덜 민감한다는 것을 보여 주었다.

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Two-Sample Inference for Quantiles Based on Bootstrap for Censored Survival Data

  • Kim, Ji-Hyun
    • 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.

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Bootstrapping Logit Model

  • Kim, Dae-hak;Jeong, Hyeong-Chul
    • Communications for Statistical Applications and Methods
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    • 제9권1호
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    • pp.281-289
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    • 2002
  • In this paper, we considered an application of the bootstrap method for logit model. Estimation of type I error probability, the bootstrap p-values and bootstrap confidence intervals of parameter were proposed. Small sample Monte Carlo simulation were conducted in order to compare proposed method with existing normal theory based asymptotic method.