• Journal of the Korean Data and Information Science Society
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• 제9권1호
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• pp.77-88
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• 1998

Smoothing spline estimators are modified to remove boundary bias effects using the technique proposed in Eubank and Speckman (1991). An O(n) algorithm is developed for the computation of the resulting estimator as well as associated generalized cross-validation criteria, etc. The asymptotic properties of the estimator are studied for the case of a linear smoothing spline and the upper bound for the average mean squared error of the estimator given in Eubank and Speckman (1991) is shown to be asymptotically sharp in this case.

• Communications for Statistical Applications and Methods
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• 제24권3호
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• pp.255-269
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• 2017

This article explores the analysis of longitudinal surveys in which same units are investigated on several occasions. Multivariate exponential ratio type estimator has been proposed for the estimation of the finite population median at the current occasion in two occasion longitudinal surveys. Information on several additional auxiliary variables, which are stable over time and readily available on both the occasions, has been utilized. Properties of the proposed multivariate estimator, including the optimum replacement strategy, are presented. The proposed multivariate estimator is compared with the sample median estimator when there is no matching from a previous occasion and with the exponential ratio type estimator in successive sampling when information is available on only one additional auxiliary variable. The merits of the proposed estimator are justified by empirical interpretations and validated by a simulation study with the help of some natural populations.

• Communications for Statistical Applications and Methods
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• 제12권1호
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• pp.169-179
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• 2005

In this study, we investigate the effects of the weight function in the bounded influence regression quantile (BIRQ) estimator for the AR(l) model with additive outliers. In order to down-weight the outliers of X -axis, the Mallows' (1973) weight function has been commonly used in the BIRQ estimator. However, in our Monte Carlo study, the BIRQ estimator using the Tukey's bisquare weight function shows less MSE and bias than that of using the Mallows' weight function or Huber's weight function. Thus, the use of the Tukey's weight function is recommended in the BIRQ estimator for our model.

• Journal of the Korean Statistical Society
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• 제32권1호
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• pp.85-92
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• 2003

We consider the partially linear model E(Y) : X$^{t}$ $\beta$＋η(Z) when the X's are measured with additive error. The semiparametric likelihood estimation ignoring the measurement error gives inconsistent estimator for both $\beta$ and η(.). In this paper we suggest the SIMEX estimator for f to correct the bias induced by measurement error, and explore its properties. We show that the rational linear extrapolant is proper in extrapolation step in the sense that the SIMEX method under this extrapolant gives consistent estimator It is also shown that the SIMEX estimator is asymptotically equivalent to the semiparametric version of the usual parametric correction for attenuation suggested by Liang et al. (1999) A simulation study is given to compare two variance estimating methods for SIMEX estimator.

• Journal of the Korean Statistical Society
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• 제25권2호
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• pp.217-233
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• 1996

This paper gives a rigorous proof of an asymptotic result about bias and variance for a transformation-based nonparametric regression estimator proposed by Park et al (1995).

• Journal of the Korean Data and Information Science Society
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• 제20권2호
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• pp.349-356
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• 2009

국내의 행정구역상 시군구 등과 같은 소지역에 있어서 실업률에 대한 남녀별 공통 상대위험도를 추정하는데, 추정방법으로 단순한 합동추정, 울프 방법에 기초한 가중추정과 잭나이프 추정들을 고려하고 이 추정 방법들의 효율성을 편의와 평균제곱오차의 개념을 통해서 비교하고자 한다. 이를 위해 2002년 12월 경기지역의 경제활동인구조사 자료를 이용하여 이 지역 내의 24개 시군단위 소지역들의 남녀별 실업률에 대한 상대위험도의 편의 및 평균제곱오차가 본 연구에서 제시된 추정절차에 의해 추정된다. 또한, 이들 추정치들의 안정성과 신뢰성은 상대편의와 상대오차제곱근을 통하여 비교된다. 추정결과 잭나이프 추정이 다른 두 추정들에 비해 매우 효율적임을 보였다.

• Communications for Statistical Applications and Methods
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• 제14권3호
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• pp.641-648
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• 2007

We propose the new sampling method, called modified ranked ordering set sampling (MROSS). Kim and Kim (2003) suggested the sign test using the ranked ordering set sampling (ROSS), and showed that the asymptotic relative efficiency (ARE) of ROSS against RSS for sign test increases as sample size does. We propose the estimator for the population mean using MROSS. The relative precision (RP) of estimator of the population mean using MROSS method with respect to the usual estimator using modified RSS is higher, and when the underlying distribution is skewed, the bias of the proposed estimator is smaller than that of several ranked set sampling estimators.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.531-550
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• 2023

The estimation of extreme quantiles is one of the main objectives of statistics of extremes (which deals with the estimation of rare events). In this paper, a robust estimator of extreme quantile of a heavy-tailed distribution is considered. The estimator is obtained through the minimum density power divergence criterion on an exponential regression model. The proposed estimator was compared with two estimators of extreme quantiles in the literature in a simulation study. The results show that the proposed estimator is stable to the choice of the number of top order statistics and show lesser bias and mean square error compared to the existing extreme quantile estimators. Practical application of the proposed estimator is illustrated with data from the pedochemical and insurance industries.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.507-518
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• 1995

The ordinary least squares based estiamte $S^2$ of the disturbance variance is considered in the linear regression model when the disturbances follow the first-order moving-average process. It is shown that $S^2$ is weakly consistent estimate for the disturbance varaince without any restriction on the regressor matrix X. Also, simple exact bounds on the relative bias of $S^2$ are given in finite sample sizes.

• Communications for Statistical Applications and Methods
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• 제18권5호
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• pp.625-636
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• 2011

본 논문에서는 로그정규분포의 엔트로피에 대한 모수적 추정량으로 최소분산비편향추정량과 최대가능도추정량을 제시하고 성질을 비교한다. 각 추정량의 분산을 유도해서 일치성을 밝히고 최대가능도 추정량의 편향이 추정에 미치는 영향을 분석한다. 델타근사방법을 이용해서 얻은 추정량의 분포를 제시하고 적합도 평가를 통한 유도한 분포의 확증을 위해서 모의실험을 수행한다. 평균제곱오차에 의한 상대적 효율성에 대한 조사를 통해 두 추정량의 성능을 비교한다. 모의실험의 결과에서 최소분산비편향추정량은 최대가능도 추정량보다 더 좋은 효율을 보이는 것으로 나타나며, 특히 표본크기와 분산이 동시에 작아짐에 따라 효율이 점점 높아지게 되어 월등히 나은 성능을 발휘함을 볼 수 있다.