• Communications for Statistical Applications and Methods
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• 제11권2호
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• pp.275-285
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• 2004

We explore classification analysis using graphical methods such as sliced inverse regression and sliced average variance estimation based on dimension reduction. Some useful information about classification analysis are obtained by sliced inverse regression and sliced average variance estimation through dimension reduction. Two examples are illustrated, and classification rates by sliced inverse regression and sliced average variance estimation are compared with those by discriminant analysis and logistic regression.

• Communications for Statistical Applications and Methods
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• 제27권1호
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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.

• Communications for Statistical Applications and Methods
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• 제23권6호
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• pp.479-496
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• 2016

In this survey, we present a modified inverse moment estimation of parameters and its applications. We use a specific model to demonstrate its principle and how to apply this method in practice. The estimation of unknown parameters is considered. A necessary and sufficient condition for the existence and uniqueness of maximum-likelihood estimates of the parameters is obtained for the classical maximum likelihood estimation. Inverse moment and modified inverse moment estimators are proposed and their properties are studied. Monte Carlo simulations are conducted to compare the performances of these estimators. As far as the biases and mean squared errors are concerned, modified inverse moment estimator works the best in all cases considered for estimating the unknown parameters. Its performance is followed by inverse moment estimator and maximum likelihood estimator, especially for small sample sizes.

• 대한기계학회논문집B
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• 제30권3호
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• pp.270-277
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• 2006

Inverse radiation problems were solved for estimating boundary temperature distribution in a way of function estimation approach in an axisymmetric absorbing, emitting and scattering medium, given the measured radiative data. In order to reduce the computational time fur the calculation of sensitivity matrix, automatic differentiation and Broyden combined method were adopted, and their computational precision and efficiency were compared with the result obtained by finite difference approximation.. In inverse analysis, the effects of the precision of sensitivity matrix, the number of measurement points and measurement error on the estimation accuracy had been inspected using quasi-Newton method as an inverse method. Inverse solutions were validated with the result acquired by additional inverse methods of conjugate-gradient method or Levenberg-Marquardt method.

• 응용통계연구
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• 제29권4호
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• pp.741-752
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• 2016

금융자산의 수익률 분포를 잘 설명할 수 있는 것으로 알려진 normal inverse Gaussian(NIG)분포는 모수의 조건에 의해 세 배의 초과첨도가 왜도 제곱의 5배보다 커야 하는데, 만약 관측된 초과첨도와 왜도의 관계가 이를 만족하지 못하거나 두 값이 매우 비슷하다면 모수를 안정적으로 추정하기 어렵게 된다. 이 논문에서 우리는 NIG분포의 모수추정에서 발생하는 이러한 문제점을 살펴보고 모의실험을 통해 이를 보정하는 방법을 찾아보았다. KOSPI, S&P500, FTSE와 HANG SENG의 실제 주가지수 자료에 적용하여 보정의 효과를 비교하고 VaR를 이용한 사후검증으로 보정된 추정방법의 성능을 평가해 보았다. 보정 방법을 이용하였을 때, 모수추정의 문제가 있던 구간을 포함한 모든 구간에서 안정적인 모수추정이 가능하였고 VaR를 통한 사후 검증에서도 분포의 성능이 떨어지지 않음을 확인하였다.

• 대한기계학회논문집B
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• 제25권5호
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• pp.673-679
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• 2001

The objective of this work is to estimate the temperature dependent thermal properties of the APC-2 composite using a inverse parameter estimation technique. The present inverse method features the estimation of the thermal conductivity and the volumetric heat capacity, which are dependent on the temperature inside the composite. Furthermore, the thermal conductivity is directionally dependent because of the aniosotropy of the composite. An on-line temperature measurement system with a suitable method of heating is built. A composite slab is fabricated using thermoplastic prepreg for the investigation. The corresponding computer code for evaluating the thermal properties inversely using the temperature reading transmitted from the measurement system is developed. The parameterized form is used for the rapid and stable estimation. The modified Newtons method is adopted for the solution technique of the inverse analysis. The estimated results are compared with the measured data from a previous study for the verification.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.267-271
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• 1996

In this study, performance improvement of the inverse modeling as the on-line control method for the estimation, control experiment is performed. As the modeling errors is occurred in duct system arbitrarily, a case using the filtered-x LMS algorithm only as the control method, a case using tile inverse modeling method only and a case using the inverse modeling with the adaptive line enhancer are compared. The estimation errors between real secondary path transfer functions and the estimated and the control performances of primary noises with these estimated transfer functions are compared.

• Communications for Statistical Applications and Methods
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• 제27권4호
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• pp.469-486
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• 2020

Entropy is an important term in statistical mechanics that was originally defined in the second law of thermodynamics. In this paper, we consider the maximum likelihood estimation (MLE), maximum product spacings estimation (MPSE) and Bayesian estimation of the entropy of an inverse Weibull distribution (InW) under a generalized type I progressive hybrid censoring scheme (GePH). The MLE and MPSE of the entropy cannot be obtained in closed form; therefore, we propose using the Newton-Raphson algorithm to solve it. Further, the Bayesian estimators for the entropy of InW based on squared error loss function (SqL), precautionary loss function (PrL), general entropy loss function (GeL) and linex loss function (LiL) are derived. In addition, we derive the Lindley's approximate method (LiA) of the Bayesian estimates. Monte Carlo simulations are conducted to compare the results among MLE, MPSE, and Bayesian estimators. A real data set based on the GePH is also analyzed for illustrative purposes.

• 한국멀티미디어학회논문지
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• 제18권7호
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• pp.886-894
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• 2015

In this paper, we conduct sensitivity analysis of parameters used for inverse modeling in order to estimate the PM₁₀ emissions from the 16 areas in East Asia accurately. Parameters used in sensitivity analysis are R, the observational error covariance matrix, and B, a priori (background) error covariance matrix. In previous studies, it was used with the predetermined parameter empirically. Such a method, however, has difficulties in estimating an accurate emissions. Therefore, an automatically determining method for the most suitable value of R and B with an error measurement criteria and posteriori emissions accuracy is required. We determined the parameters through a sensitivity analysis, and improved the accuracy of posteriori emissions estimation. Inverse modeling methods used in the emissions estimation are pseudo inverse, NNLS (Nonnegative Least Square), and BA(Bayesian Approach). Pseudo inverse has a small error, but has negative values of emissions. In order to resolve the problem, NNLS is used. It has a unrealistic emissions, too. The problems are resolved with BA(Bayesian Approach). We showed the effectiveness and the accuracy of three methods through case studies.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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• pp.182-185
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• 1996

The purpose of slate estimation in power system is to estimate the best-fit Slate variables from the measurements contaminated by various kind of noise. But because the majority of state estimation modules in EMS lack the convergence characteristics, sometimes the desirable outputs can't be obtained. So, in this paper, the new algorithm using the load now output as initial values in the state estimation calculation is proposed to guarantee the convergence. And if the load now outputs were used as the initial values in the calculation, the change in each step would be small compared to the original method using the flat start point. And the Inverse Lemma is used in the algorithm to calculate the new stale in each iteration step for reducing the calculation time. The proposed algorithm was tested on the IEEE 14, 30, 118 bus systems. Eventually, we were able to verity that the differences between the results obtained by the original method and proposed method were relatively small, and the effectiveness of the proposed algorithm increased when applied to the bigger systems.