• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.11-19
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• 2002

In this paper, the problem of estimating a p-variate $(p\geq4)$ normal mean vector in a decision-theoretic setup is considered. Using a technique of Guo and Pal (1992), a sequence of estimators dominating the Lindley type estimator is derived and each improved estimator is better than the previous one.

• 대한수학회논문집
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• 제11권4호
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• pp.1187-1192
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• 1996

It is known that an unbiased estimator of f(p) for binomial B(n,p) exists if and only if f is a polynomial of degree at most n, in which case the unbiased estimator of a real-valued function $f(p), p = (p_0,p_1,\cdots,p_r)$ is unique. In general, this estimator has the serious fault of not being range preserving; that is, its value may fall outside the range of f(p). In this article, a condition on a real-valued function f is derived that is necessary for the unbiased estimator to be range preserving that this is sufficient when n is large enough.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.129-134
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• 2004

In this study, we investigate the effects of the weight function in the bounded influence regression quantile (BIRQ) estimator for the AR(1) 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.

• Journal of the Korean Statistical Society
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• 제31권2호
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• pp.229-235
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• 2002

A generalized Stein-rule estimator of the vector of regression coefficients in linear regression model is considered and its properties are analyzed according to the criterion of Pitman nearness. A comparative study shows that the generalized Stein-rule estimator representing a class of estimators contains particular members which are better than the usual Stein-rule estimator according to the Pitman closeness.

• 응용통계연구
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• 제6권1호
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• pp.79-93
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• 1993

회귀모형에 있어서의 Ruppert와 Carroll의 절사 회귀 추정법을 확장하여 회귀 분위수에 의 한 두 개의 두분으로 관측치를 분할하여 각 부분마다 가중치를 달리 부여하는 방법으로 적 합된 L-추정법을 제안하였다. 이 제안된 L-추정법은 특히 비대칭인 오차분포하에서 좋은 효율을 가지고 있었다.

• 응용통계연구
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• 제21권5호
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• pp.889-900
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• 2008

Child labour is a disturbing issue for any society. It is attempted here in this article to develop an estimator to assess the numerical strength of this menace in Lahore division. A Horvitz and Thompson (1952) type of estimator is developed where weights are calculated on the basis of poverty and illiteracy to increase the sampling efficiency. Different characteristic features of this estimator, like its unbiasedness, variance, probability distribution, confidence intervals are also developed for its study from different angles.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 춘계학술대회
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• pp.109-119
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• 2003

In this paper we propose a local smoothing of the Nelson type estimator for the survival function based on an approximation by the Weibull distribution function. It appears that Mean Square Error and Bias of the smoothed estimator of the Nelson type survival function estimator is significantly smaller then that of the smoothed estimator of the Kaplan-Meier survival function estimator.

• Journal of applied mathematics & informatics
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• 제13권1_2호
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• pp.501-508
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• 2003

Although the estimate of regression function is important, some have focused the variance estimation of error term in regression model. Different variance estimators perform well under different conditions. In many practical situations, it is rather hard to assess which conditions are approximately satisfied so as to identify the best variance estimator for the given data. In this article, we suggest SHM estimator compared to LS estimator, which is common estimator using in parametric multiple regression analysis. Moreover, a combined estimator of variance, VEM, is suggested. In the simulation study it is shown that VEM performs well in practice.

• 응용통계연구
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• 제25권5호
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• pp.793-802
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• 2012

One proposal is made to construct a nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of the idea of minimizing approximate variance of a proposed estimator using regression quantiles. This nonparametric estimator and some other L-estimators are studied and compared with well known M-estimators through a simulation study.

• 소음진동
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• 제9권6호
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• pp.1240-1246
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• 1999

A prior error estimator which is solving structural dynamic problems and which is based on the generalized-method, is developed. Since the proposed error estimator is computed with only previous information, the time step size can be adaptively selected without the feedback mechanism. This paper shows that the automatic time stepping algorithm using the error estimator performs an efficient time integration. To verify its efficiency, several examples are numerically investigated.