• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.123-130
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• 2003

We define a broad class of rotation designs whose monthly sample is balanced in interview time, level of recall, and rotation group, and whose rotation scheme is time-invariant. The necessary and sufficient conditions are obtained for such designs. Using these conditions, we derive a minimum variance unbiased generalized composite estimator (MVUGCE). To examine the existence of time-in-sample bias and recall bias, we also propose unbiased estimators and their variances. Numerical examples investigate the impacts of design gap, non-sampling error sources, and two types of correlations on the variance of MVUGCE.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.8
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• pp.557-562
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• 1988

This paper presents a class of discrete adaptive controller that can be applied to a plant without sufficient a priori information. It is well known that the GMV(Generalized Minmum Variance) contrlller performs satisfactorily if the plant time delay is known. By introducing the long-range prediction into the GMV controller, robustness to the time delay can be improved, although optimality is lost. Such an idea motivates a predictive control system to be proposed here, where the system minimizes multi-stage cost via the GMV approach. Moreover, the detuning control weight is determined by an on-line tuning method. It is shown that robustness, computational efficiency, and performance of the resulting control system are improved as compared with those of the GPC(Generalized Predictive Control)system.

• Journal of Korean Society for Quality Management
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• v.23 no.2
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• pp.28-42
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• 1995

For quality improvement, Taguchi emphasizes the reduction of variation of the quality characteristic, Taguchi has used the signal-to-noise ratios for achieving minimum dispersion of the quality characteristic with its location adjusted to some desired target value ${\tau}$ Lim(1994) proposes a reasonable SN ratio based on a linking relationship of the variance and mean through simple data analysis technique. In this paper we investigate the efficiency of those two SN ratios and variance stabilizing transformations through Monte Carlo Simulations.

• Journal of Korean Society for Quality Management
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• v.10 no.1
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• pp.2-6
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• 1982

Suppose a system with m components is subjected to a random stress. We consider the estimation of reliability when data consist of random samples from the stress distribution and the strength distributions. All the distributions are assumed to be independent exponential with unknown scale parameters. An explicit form of system reliability and the minimun variance unbiased estimator are obtained. The asymptotic distribution is also obtained by expanding the minimum variance unbiased estimator about the maximum likelihood estimator and establishing their equivalance. The performance of the two estimators is compared by Monte Carlo Simulation.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.123-134
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• 2007

This paper focuses on the in-house reliability assurance plan for the bulk materials of each company. The reliability assurance needs in essence a long time and high cost for testing the materials. In order to reduce the time and cost, accelerated life test is adopted. The bulk sampling technique was used for acceptance. Design parameters might be total sample size(segments and increments}, stress level and so on. We focus on deciding the sample size by minimizing the asymptotic variance of test statistics as well as satisfying the consumer's risk. In bulk sampling, we also induce the sample size by adapting the normal life time distribution model when the variable of the lognormal life time distribution is transformed and adapted to the model. In addition, the sample size for both the segments and increments can be induced by minimizing the asymptotic variance of test statistics of the segments and increments with consumer's risk met. We can assure the reliability of the mean life and B100p life time of the bulk materials by using the calculated minimum sample size.

• Journal of the Korean Data and Information Science Society
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• v.1
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• pp.67-76
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• 1990

For a two-parameter Pareto distribution, the uniformly minimum variance unbiased estimateors(UMVUE) for the function of the two parameters are expressed in terms of confluent hypergeometric function. The variance of the UMVUE is also expressed in terms of hypergeometric function of several variables. UMVUE's for the ${\gamma}th$ moment about zero and several useful parametric functions, and their variances are obtained as special cases. The estimators of Baxter(1980) and Saksena and Johnson(1984) are special cases of our estimator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.1097-1106
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• 1997

Most works on importance sampling (IS) as an efficient evaluation technique havd been done in an additibe white gaussian noise channel (Awgn). In this paper we propose a CQ(conventional importance sampling and quasi-translantion) IS technique for the mobile radio channel modeled as Rician fading, and analyze the IS estimator's variance to determine optimum IS parameters and the minimum number of run times. Reference showed that CIS technique has a poor performance for systems with meories, but it is shown that the CIS technique can be improved by combining with quasi-translation technique even for systems with memories. Here the CQ IS technique modifies the variance of additive noise and also performs quasi-translation for the fading distribution. We determine the optimum IS parameters of the proposed CQ IS estimator and whow that the simulation gains are about 10$^{3}$~10$^{6}$ for the mobile communication systems with memories in case of the expected BERs 10$^{-5}$ ~10$^{-8}$ .

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2733-2746
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• 2018

The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.

• The Korean Journal of Ecology
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• v.17 no.3
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• pp.379-385
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• 1994

Sonograms of songs recorded in Kwangnung and Chejudo were analyzed to investigate the features and variances in the songs of Great tit, Parus major variety. Songs of Great tits were identified, most of which were repetitions of phrases compoed of high-frequency note and low-frequency note. Variances between the songs of the two areas in the minimum and maximum of low-frequency were significat. The CV range of the Great tit group in Chejudo was wider than that in Kwangnung. Interregional variance level was significant in the minimum (P<0.04) and maximum (P<0.0001) of low-frequency.

• Journal of Magnetics
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• v.15 no.2
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• pp.74-77
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• 2010

This paper deals with optimum design criteria for maximum torque density & minimum torque ripple of a Flux Switching Motor (FSM) using response surface methodology (RSM) & finite element method (FEM). The focus of this paper is to find a design solution through the comparison of torque density and torque ripple which vary with rotor shape. And then, a central composite design (CCD) mixed resolution was introduced and analysis of variance (ANOVA) was conducted to determine the significance of the fitted regression model. The proposed procedure allows one to define the rotor dimensions, starting from an existing motor or a preliminary design.