• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.311-319
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• 2013

Cooray and Ananda (2005) proposed a composite lognormal-Pareto model to analyze loss payment data in the actuarial and insurance industries. Their model is based on a lognormal density up to an unknown threshold value and a two-parameter Pareto density. In this paper, we implement the minimum density power divergence estimation for the composite lognormal-Pareto density. We compare the performances of the minimum density power divergence estimator (MDPDE) and the maximum likelihood estimator (MLE) by simulations and an example. The minimum density power divergence estimator performs reasonably well against various violations in the distribution. The minimum density power divergence estimator better fits small observations and better resists against extraordinary large observations than the maximum likelihood estimator.

• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.147-161
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• 2016

This paper introduces the four parameter new generalized inverse Weibull distribution and investigates the potential usefulness of this model with application to reliability data from engineering studies. The new extended model has upside-down hazard rate function and provides an alternative to existing lifetime distributions. Various structural properties of the new distribution are derived that include explicit expressions for the moments, moment generating function, quantile function and the moments of order statistics. The estimation of model parameters are performed by the method of maximum likelihood and evaluate the performance of maximum likelihood estimation using simulation.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.61-63
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• 1994

Accurate estimation of soil resistivity parameters are very important in the design of grounding systems. This paper presents a useful methodology for the optimal estimation of soil parameters based on the weighted least square concepts using a set of earth resistivity measurements by Wenner method. And, this paper developes a computer simulation programming for the estimation of soil parameters. Results are presented and compared with the results of other methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.112-119
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• 2010

This paper defines the probability models for determining the disparity map given stereo images and derives the methods for solving the problem, which is proven to be equivalent to an energy-based stereo matching. Under the assumptions the difference between the pixel on the left image and the corresponding pixel on the right image and the difference between the disparities of the neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameter is proposed. Usually energy-based stereo matching methods are so sensitive to the parameter that it should be carefully determined. The proposed method alternates between estimating the parameter with the intermediate disparity map and estimating the disparity map with the estimated parameter, after computing it with random initial parameter. It is shown that the parameter estimated by the proposed method converges to the optimum and its performance can be improved significantly by adjusting the parameter and modifying the energy term.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.483-494
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• 2013

The importance of financial risk management has been highlighted after several recent incidences of global financial crisis. One of the issues in financial risk management is how to measure the risk; currently, the most widely used risk measure is the Value at Risk(VaR). We can consider to estimate VaR using extreme value theory if the financial data have heavy tails as the recent market trend. In this paper, we study estimations of VaR using Peaks over Threshold(POT), which is a common method of modeling fat-tailed data using extreme value theory. To use POT, we first estimate parameters of the Generalized Pareto Distribution(GPD). Here, we compare three different methods of estimating parameters of GPD by comparing the performance of the estimated VaR based on KOSPI 5 minute-data. In addition, we simulate data from normal inverse Gaussian distributions and examine two parameter estimation methods of GPD. We find that the recent methods of parameter estimation of GPD work better than the maximum likelihood estimation when the kurtosis of the return distribution of KOSPI is very high and the simulation experiment shows similar results.

• Smart Media Journal
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• v.2 no.2
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• pp.33-38
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• 2013

In this paper, we investigated baseline estimation methods for remove background noise using Raman spectra from acute alcohol liver injury and acute ethanol-induced chronic liver fibrosis. Far the baseline estimation, we applied first derivative, linear programming and rolling ball method. Optimal input parameter of each method were determined by the training rate of MAP (maximum a posteriori probability) classifier. According to the experimental results, classification results baseline estimation with the rolling ball algorithm gave about 89.4%, which is very promising results for classification of acute alcohol liver injury and acute ethanol-induced chronic liver fibrosis. From these results, to determined the appropriate methods and parameters of baseline estimation impact on classification performance was confirmed.

• The Research Journal of the Costume Culture
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• v.14 no.5
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• pp.840-849
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• 2006

Breast volume has been approximately estimated under the assumption that the shape of breast is a corn. However, women's breast is more like a bulged bag in reality. In this paper, three methods of breast volume estimation were compared to find out the more accurate method. The shape of the breast is assumed as a hemisphere in the first estimation method and a corn in the second one. In the third method, arc along the cross sectional shape of breast was utilized in the calculation. Comparisons among the methods were made using the actual 3D volume measurement of thirty seven women's breast. As results, the third method was the best one for the normal breast type, especially for the lower part of the breast ($R^2=0.74$) which is the crucial design parameter of the brassiere. Assumption of the shape of breast as a corn was reasonably acceptable when the breast is sagged. It was expected that when women wore brassiere, the accuracy of the third method would increase more, since the shape of breast becomes more symmetrical.

• Journal of Communications and Networks
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• v.15 no.5
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• pp.496-503
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• 2013

In an orthogonal frequency division multiplexing system, conventional interpolation techniques cannot correctly balance performance and overhead when estimating dynamic long-delay channels in single frequency networks (SFNs). In this study, classical filter analysis and design methods are employed to derive a complex interpolator for maximizing the resistible echo delay in a channel estimator on the basis of the correlation between frequency domain interpolating and time domain windowing. The coefficient computation of the complex interpolator requires a key parameter, i.e., channel length, which is obtained in the frequency domain with a tentative estimation scheme having low implementation complexity. The proposed complex adaptive interpolator is verified in a simulated digital video broadcasting for terrestrial/handheld receiver. The simulation results indicate that the designed channel estimator can not only handle SFN echoes with more than $200{\mu}s$ delay but also achieve a bit-error rate performance close to the optimum minimum mean square error method, which significantly outperforms conventional channel estimation methods, while preserving a low implementation cost in a short-delay channel.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.4
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• pp.374-383
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• 2020

At ship design stage, the maneuverability is generally estimated based on the empirical formula or the computational fluid dynamic (CFD), which is one of the numerical simulation methods. Using the hydrodynamic derivatives derived through these methods can quantitatively estimate the maneuverability of target vessels and evaluate indirect maneuverability. Nevertheless, research on estimating maneuverability is insufficient for ships not subject to IMO maneuverability standard, especially fishing vessels, and even at the design stage, the empirical formula developed for merchant ships is applied without modification. An estimation error may occur due to the empirical formula derived from the regression analysis results of a model test if the empirical formula developed for merchant ships with different hull shapes is applied to fishing vessels without any modification. In this study, the modified empirical formula that can more accurately estimate the fishing vessel's maneuverability was derived by including the hull shape parameter of target fishing trawlers in the regression analysis process that derives Kijima et al. (1990) formula. As a result, the modified empirical formula showed an average estimation error of 6%, and the result improved the average error of 49% of Kijima et al. (1990) formula developed for merchant ships.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1918-1924
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• 2010

This In this paper, we propose an efficient algorithm for motion estimation of the image sequences with luminance fluctuation. For such sequences, conventional motion estimation methods based on the difference of pixel values usually produce the erroneous motion information. The proposed algorithm defines the luminance fluctuation as a linear model with gain and offset parameter, and extracts motion information using gradient and phase of the corresponding local region within consecutive frames. Therefor the method is robust to the luminance change of the frames. We test our algorithm for the ground truth sequence with artificially added luminance change and motion, and real sequences corrupted by the flicker. The results shows that the proposed algorithm outperforms the conventional methods.