• 제목/요약/키워드: Nonparametric Estimation

검색결과 211건 처리시간 0.031초

SMOOTH NONPARAMETRIC ESTIMATION OF MEAN RESIDUAL LIFE

  • Na, Myoung-Hwan;Park, Sung-Hyun;Kim, Jae-Joo
    • 한국품질경영학회:학술대회논문집
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    • 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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    • pp.571-579
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    • 1998
  • In this paper we propose smooth nonparametric estimator of Mean Residual Life(MRL) based on a complete sample. This estimator is constructed using estimator of cumulative failure rate which is derived as the maximum likelihood estimate of cumulative failure rate in the class of distributions which have piecewise linear failure rate functions between each pair of observations. We derive the asymptotic properties of the our estimator. The proposed estimator is compared with previously known estimator by Monte Carlo study.

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On the Equality of Two Distributions Based on Nonparametric Kernel Density Estimator

  • Kim, Dae-Hak;Oh, Kwang-Sik
    • Journal of the Korean Data and Information Science Society
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    • 제14권2호
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    • pp.247-255
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    • 2003
  • Hypothesis testing for the equality of two distributions were considered. Nonparametric kernel density estimates were used for testing equality of distributions. Cross-validatory choice of bandwidth was used in the kernel density estimation. Sampling distribution of considered test statistic were developed by resampling method, called the bootstrap. Small sample Monte Carlo simulation were conducted. Empirical power of considered tests were compared for variety distributions.

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Optimal Design for Locally Weighted Quasi-Likelihood Response Curve Estimator

  • Park, Dongryeon
    • Communications for Statistical Applications and Methods
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    • 제9권3호
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    • pp.743-752
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    • 2002
  • The estimation of the response curve is the important problem in the quantal bioassay. When we estimate the response curve, we determine the design points in advance of the experiment. Then naturally we have a question of which design would be optimal. As a response curve estimator, locally weighted quasi-likelihood estimator has several more appealing features than the traditional nonparametric estimators. The optimal design density for the locally weighted quasi-likelihood estimator is derived and its ability both in theoretical and in empirical point of view are investigated.

A Note on Asymptotic Relative Efficiency of the Nonparametric Reliability Estimation for the Proportional Hazards Model

  • Cha, Young-Joon;Lee, Jae-Man;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • 제9권2호
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    • pp.173-177
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    • 1998
  • This paper presents the asymptotic relative efficiency of the nonparametric estimator relative to the parametric maximum likelihood estimator of the reliability function under the proportional hazards model of random censorship. Also we examine the efficiency loss due to censoring proportions and misson times.

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Nonparametric Estimation of Bivariate Mean Residual Life Function under Univariate Censoring

  • Dong-Myung Jeong;Jae-Kee Song;Joong Kweon Sohn
    • Journal of the Korean Statistical Society
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    • 제25권1호
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    • pp.133-144
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    • 1996
  • We, in this paper, propose a nonparametric estimator of bivariate mean residual life function based on Lin and Ying's (1993) bivariate survival function estimator of paired failure times under univariate censoring and prove the uniform consistency and the weak convergence result of this estimator. Through Monte Carlo simulation, the performances of the proposed estimator are tabulated and are illustrated with the skin grafts data.

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Nonparametric Reliability Estimation in Strength-Stress Model: B-Spline Approach

  • Kim, Jae-Joo;Na, Myung-Hwan;Lee, Kang-Hyun
    • 품질경영학회지
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    • 제27권2호
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    • pp.152-162
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    • 1999
  • In this paper we develope a new nonparametric estimator of the reliability in strength-stress model. This estimator is constructed using the maximum likelihood estimate of cumulative failure rate in the class of distributions which have piecewise linear failure rate functions between each pair of observations. Large sample properties of our estimator are examined. The proposed estimator is compared with previously known estimator by Monte Carlo study.

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Nonparametric Estimation of Reliability in Time Dependent Strength-Stress Model

  • Lee, Hyun-Woo;Na, Myung-Hwan
    • Journal of the Korean Data and Information Science Society
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    • 제10권1호
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    • pp.111-118
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    • 1999
  • We treat the problem of estimating reliability R(t) = P[Y(t) < X(t)] in the time dependent strength-stress model in which a unit of strength X(t) is subjected to environmental stress Y(t) at time t. In this paper two nonparametric approaches to estimate of R(t) are analyzed and compared with parametric method by simulation.

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NONPARAMETRIC DISCONTINUITY POINT ESTIMATION IN GENERALIZED LINEAR MODEL

  • Huh, Jib
    • Journal of the Korean Statistical Society
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    • 제33권1호
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    • pp.59-78
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    • 2004
  • A regression function in generalized linear model may have a discontinuity/change point at unknown location. In order to estimate the location of the discontinuity point and its jump size, the strategy is to use a nonparametric approach based on one-sided kernel weighted local-likelihood functions. Weak convergences of the proposed estimators are established. The finite-sample performances of the proposed estimators with practical aspects are illustrated by simulated examples.

Weighted Estimation of Survival Curves for NBU Class Based on Censored Data

  • Lee, Sang-Bock
    • Journal of the Korean Data and Information Science Society
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    • 제7권1호
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    • pp.59-68
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    • 1996
  • In this paper, we consider how to estimate New Better Than Used (NBU) survival curves from randomly right censored data. We propose several possible NBU estimators and study their properties. Numerical studies indicate that the proposed estimators are appropriate in practical use. Some useful examples are presented.

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선형 응답률 모형에서 초모집단 모형의 비모수적 함수 추정을 이용한 무응답 편향 보정 추정 (Bias corrected non-response estimation using nonparametric function estimation of super population model)

  • 심주용;신기일
    • 응용통계연구
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    • 제34권6호
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    • pp.923-936
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    • 2021
  • 표본조사에서는 다수의 무응답이 발생하며 이를 적절히 처리하는 다양한 방법이 개발되었다. 특히 무응답이 관심변수에 영향을 받고 이로 인해 발생한 편향은 추정의 정확성을 크게 떨어뜨리며 무응답 처리를 어렵게 한다. 최근 Chung과 Shin (2017, 2020)은 알려진 모수적 초모집단 모형과 응답률 모형을 이용하여 추정의 정확성을 향상한 추정량을 제안하였다. 본 연구에서는 초모집단 모형의 형태를 일반화하여 비모수적 함수 형태를 설정한 후 이를 기반으로 얻어진 편향을 적절히 처리한 편향 보정 평균추정량을 제안하였다. 모의실험을 통해 본 연구에서 제안한 방법의 우수성을 확인하였다.