• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.291-301
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• 2017

It is well known in a small sample that the maximum likelihood (ML) approach for variance components in the general linear model yields estimates that are biased downward. The ML estimate of residual variance tends to be downwardly biased. The underestimation of residual variance, which has implications for the estimation of marginal effects and asymptotic standard error of estimates, seems to be more serious in some limited dependent variable models, as shown by some researchers. An alternative frequentist's approach may be restricted or residual maximum likelihood (REML), which accounts for the loss in degrees of freedom and gives an unbiased estimate of residual variance. In this situation, the REML estimator is derived in a censored regression model. A small sample the REML is shown to provide proper inference on regression coefficients.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.97-108
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• 2020

This paper compares several methods for estimating parameters of normal inverse Gaussian distribution. Ordinary maximum likelihood estimation and the method of moment estimation often do not work properly due to restrictions on parameters. We examine the performance of adjusted estimation methods along with the ordinary maximum likelihood estimation and the method of moment estimation by simulation and real data application. We also see the effect of the initial value in estimation methods. The simulation results show that the ordinary maximum likelihood estimator is significantly affected by the initial value; in addition, the adjusted estimators have smaller root mean square error than ordinary estimators as well as less impact on the initial value. With real datasets, we obtain similar results to what we see in simulation studies. Based on the results of simulation and real data application, we suggest using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values to estimate the parameters of normal inverse Gaussian distribution.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.50-52
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• 2006

This paper Proposes a new method of on-line estimation for rotor resistance of the induction motor in the indirect vector controlled drive, using artificial neural network (ANN). The back propagation algorithm is used for training of the neural networks. The error between the desired state variable of an induction motor and actual state variable of a neural network model is back propagated to adjust the weight of a neural network model, so that the actual state variable tracks the desired value. The performance of rotor resistance estimator and torque and flux responses of drive, together with these estimators, are investigated variations rotor resistance from their nominal values. The rotor resistance are estimated analytically, using the proposed ANN in a vector controlled induction motor drive.

• Journal of electromagnetic engineering and science
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• v.18 no.3
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• pp.169-174
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• 2018

In this paper, we propose an estimation method using multiple in-phase and quadrature (IQ) signals of different frequencies to evaluate the sample-time errors in the sampling oscilloscope. The estimator is implemented by ODRPACK, and a novel iteration scheme is applied to achieve fast convergence without any prior information. Monte-Carlo simulation is conducted to confirm the proposed method. It clearly shows that the multiple IQ approach achieves more accurate results compared to the conventional method. Finally, the criteria for the frequency selection and the signal capture time are investigated.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1191_1192
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• 2009

The objective of levitation control design is to stabilize a levitation system, or obtain certain transient response, bandwidth, and steady state error. An air gap signal from the each corner is important parameter to design levitation controller. A levitation controller using gap signals with measurement delay time can not make a expected performance. In this paper, a new air gap estimator to improve the performance of levitation controller is proposed. The estimated gap signal which has little measurement delay time is used as a feedback value in the levitation controller.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.918-920
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• 2001

PMSM drives are widely used in industrial and residential applications because of high efficiency, high power density and high performance. For better performance of PMSM, however, torque ripples should be reduced. This paper investigates a reduction of torque ripple due to the unsinusoidal flux linkage produced by the shapes of stator slot and magnetic pole. To minimize torque ripple, a simple flux estimator is proposed. This method iteratively compensates the distributed flux linkage from an error between the measured and estimated currents. The proposed algorithm is verified through simulation.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.319-324
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• 2003

본 논문에서는 matched-pair design에서의 두 처리간 동등성/ 비열등성 검정에 대해 고려하였다. 기존에 비율차이나 risk ratio관점에서 동등성/비열등성 검정을 시행한 것과는 달리, 본 논문에서는 odds ratio에 기초하여 두 가지 검정통계량을 유도하였다. (1) constrained maximum likelihood estimator(mle)를 이용한 fieller type 통계량 (2) 제약없이 구한 mle를 사용한 wald-type 통계량). 비율 차이나 risk ratio에 기초한 기존의 통계적 방법들(비율차이에 근거한 (3) score-type 통계량과 (4) wald-type 통계량, risk ratio에 기초한 (5) fieller-type 통계량과 (6) wald-type 통계량)과 본 논문에서 제시한 두가지 통계량의 성능을 비교하기 위해 모의실험을 시행하였다. 모의실험 결과, 본 논문에서 제안한 constrained mle를 사용한 fieller type 통계량은 empirical type I error 측면에서 매우 만족스러운 결과를 보이고 있으며, 특히 비대각 셀의 확률이 작아질 경우에도 안정적인 성능을 보여준다.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.89-98
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• 1999

In this paper we estimate the reliability of parallel system with two components. We assume that the strengths of these components follow bivariate exponential(BVE) models proposed by Marshall-Olkin(1967) Block-Basu(1974) Freund(1961) and Proschan-Sullo(1974) These two components are subjected to a normally distributed random stress which is independent of the strength of the components. If the strengths ($\textit{X}_1$, $\textit{X}_2$) are subjected to a stress($\textit{Y}$) then the system reliability ($\textit{R}$) is given by $\textit{R}=\textit{P}[\textit{Y} We present some numerical results and compare the bias and the mean square error of the maximum likelihood estimator and proposed estimators for a moderate sized samples when $(\textit{X}_1, \textit{X}_2)$ follow BVE of Marshall-Olkin.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.403-413
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• 2012

The modifications suggested in Uhm et al. (2011) are studied using a partly parametric version of Aalen's additive risk model. A follow-up time period is partitioned into intervals, and hazard functions are estimated as a piecewise constant in each interval. A maximum likelihood estimator by iteratively reweighted least squares and variance estimates are suggested based on the model as well as evaluated by simulations using mean square error and a coverage probability, respectively. In conclusion the modifications are needed when there are a small number of uncensored deaths in an interval to estimate the piecewise constant hazard function.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.314-320
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• 2012

This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.