• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.91-102
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• 2019

In this paper, we propose a new estimation method based on a weighted linear regression framework to obtain some estimators for unknown parameters in a two-parameter Rayleigh distribution under a progressive Type-II censoring scheme. We also provide unbiased estimators of the location parameter and scale parameter which have a nuisance parameter, and an estimator based on a pivotal quantity which does not depend on the other parameter. The proposed weighted least square estimator (WLSE) of the location parameter is not dependent on the scale parameter. In addition, the WLSE of the scale parameter is not dependent on the location parameter. The results are compared with the maximum likelihood method and pivot-based estimation method. The assessments and comparisons are done using Monte Carlo simulations and real data analysis. The simulation results show that the estimators ${\hat{\mu}}_u({\hat{\theta}}_p)$ and ${\hat{\theta}}_p({\hat{\mu}}_u)$ are superior to the other estimators in terms of the mean squared error (MSE) and bias.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.829-832
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• 2001

본 논문에서는 2차 통계치를 이용하여 패널추징 및 등화 기법을 제안하였다. 기존의 채널 추정 알고리듬은 잡음이 없는 환경에서 LS방법을 이용하기 때문에 잡음이 강한 패널에서는 원하는 성능을 얻을 수 없는 단점이 있다. 수신신호의 상관행렬의 최소 고유값에 대응하는 고유벡터는 채널의 임펄스 응답에 관한 정보를 포함하고 있다. 이러한 고유 벡터를 매시간마다 갱신시키면서 구하는 적응 알고리듬을 제안하고 이를 이용하여 블라인드 채널 추정 및 등화기 파라미터를 추정하였다. 제안한 알고리듬은 잡음에 강인한 특성을 보일 뿐 아니라 기존의 알고리듬들 보다 우수한 채널 추정 및 등화 성능을 모의 실험을 통하여 검증하였다.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.55-63
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• 1989

In this paper we present the shrunken testing estimator for the variance of normal population and we find the condition that can be used in seeking the situations in which the proposed estimator is superior to the minimum variance unbiased estimator.

• Journal of the Korean Statistical Society
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• v.24 no.1
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• pp.161-181
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• 1995

The goal of this article is to study the performances of various empirical Bayes simultaneous interval estimates for all pairwise comparisons. The considered empirical Bayes interval estimaters are those based on unbiased estimate, a hierarchical Bayes estimate and a constrained hierarchical Bayes estimate. Simulation results for small sample cases are given and an illustrative example is also provided.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.285-292
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• 1999

In this paper we propose the several estimators of the Lorenz curve in the Pareto distribution and obtain the bias and the mean squared error for each estimator. We compare the proposed estimators with the uniformly minimum variance unbiased estimator (UMVUE) and the maximum likelihood estimator (MLE) in terms of the mean squared error (MSE) through Monte Carlo methods and discuss the results.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.79-83
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• 1997

This paper considers the problem of estimating the model parameters and reliability functions for Freund bivariate exponential distribution. Uniformly minimum variance unbiased estimators for model parameters, joint reliability and marginal reliability functions are obtained in the both case of non-identically distributed marginals and identically distributed marginals.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1179-1189
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• 2007

In this paper, we estimate the proportion of individuals having health insurance in a given year for several small domains cross-classified by age, sex and other demographic characteristics using the data provided by the National Center for Health Statistics(NCHS). We employ Bayesian as well as frequentist methodology to obtain small domain estimates and the associated measures of precision. One of the new features of our study is that we utilize the survey weights along with the model to derive the small domain estimates.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.659-667
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• 2013

If the regression model or the propensity model is correct, the unbiasedness of the estimator using doubly robust imputation can be guaranteed. Using a neural network instead of a logistic regression model for the propensity model, the estimators using doubly robust imputation are approximately unbiased even though both assumed models fail. We also propose a doubly robust estimator of ratio form using population information of an auxiliary variable. We prove some properties of proposed theory by restricted simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.214-217
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• 1987

In this paper self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in multiple ARMA process. This process is simplified as independent SISO ARMA process having offset terms. This offset was considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the parameter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results considers well with the analysis in case of linear interconnection.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.12
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• pp.879-883
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• 1988

In this paper, self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in MIMO ARMA procss. This process is simlified as independent SISO ARMA processes having offset terma, which are considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the paramter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results consider well with the analysis in case of linear interconnection.