• Journal of applied mathematics & informatics
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• 제22권1_2호
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• pp.133-148
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• 2006

This paper proposes a smoothing method for symmetric conic linear programming (SCLP). We first characterize the central path conditions for SCLP problems with the help of Chen-Harker-Kanzow-Smale smoothing function. A smoothing-type algorithm is constructed based on this characterization and the global convergence and locally quadratic convergence for the proposed algorithm are demonstrated.

• 소음진동
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• 제7권5호
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• pp.747-756
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• 1997

Wigner-Ville distribution which is a time-frequency analysis has a fatal drawback, when the signal has multiple components. This is the cross-talk and often causes a neagative value in the distribution. Wingner-Ville distriution is an expression of power, therefore the cross-talk must be avoided. Smoothing the Wigner-Ville distribution by convoluting it with a window, is most commonly used to reduce the cross-talk. There can be infinite number of distributions depending on the windows. But, the smoothing reduces resolution in time-frequency plane; this motives to design a more effective window in reducing cross-talk while remaining resolution. The domain in which the cross-talk and legitimate components can be easily distinguished, is the ambiguity function. In the ambiguity function domain, the legitimate components appear as linear lines passing through the orgine. But, the cross-talk is widely distributes in the ambiguity function plane. Based on the relative distributions of cross-talk and legitimate components, rotating window can be designed to minimize cross-talk. Applying the rotating window to the ambiguity function corresponds to smoothing the Wigner-Ville distribution. Therefore, the effects of rotating window is estimated in terms of the bias error due to smooting the Wigner-Ville distribution. By applying the rotating window, not only the Wigner-Ville distribution but also its properties are changed. The properties of the new distribution are checked, in order to complete analyzing the rotating window.

• Communications for Statistical Applications and Methods
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• 제23권3호
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• pp.189-201
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• 2016

In survival analysis, the Nelson-Aalen estimator and Peterson estimator are often used to estimate a cumulative hazard function in randomly right censored data. In this paper, we suggested the smoothing version of the cumulative hazard function estimators using a Bezier curve. We compare them with the existing estimators including a kernel smooth version of the Nelson-Aalen estimator and the Peterson estimator in the sense of mean integrated square error to show through numerical studies that the proposed estimators are better than existing ones. Further, we applied our method to the Cox regression where covariates are used as predictors and suggested a survival function estimation at a given covariate.

• Communications for Statistical Applications and Methods
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• 제4권3호
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• pp.911-915
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• 1997

The purpose of this paper is to consider the problem of selection of optimal smoothing parameter for kernel-type distribution function estimator, which asymptotically minimizes mean Hellinger distance.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권2호
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• pp.78-89
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• 2016

Purpose: In this paper, we investigate whether the endeavors for Six Sigma quality management by a firm have positive effects on its financial performance and the length of Six Sigma implemented period affects its financial status. We find a relationship between Six Sigma implemented period and several financial performance index using a smoothing spline function. Methods: A smoothing spline function is used in order to analyze the relationship between efforts for quality management and financial performance. Specifically, the return on assets, return on equity, sales cost and business fee are investigated as dependent variables and the efforts for quality management as independent variable. Results: As a result of the analysis, the indication is that companies that put effects into the Six Sigma quality management have a positive result in its financial status. In detail, the efforts for Six Sigma quality management have positive effects on total asset turnover ratio and Six Sigma implemented period on net income to net sales ratio. Additionally, companies with longer (shorter) period of Six Sigma program have more (less) improvement in its financial status. Conclusion: It can be concluded that the company's efforts for quality management positively influence financial performance.

• Industrial Engineering and Management Systems
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• 제8권4호
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• pp.257-263
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• 2009

Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent to (1, 1) order ARMA model equation, new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Theoretical solution was derived in a simple way. Mere application of ESM does not make good forecasting accuracy for the time series which has non-linear trend and/or trend by month. A new method to cope with this issue is required. In this paper, combining the trend removal method with this method, we aim to improve forecasting accuracy. An approach to this method is executed in the following method. Trend removal by a linear function is applied to the original shipping data of consumer goods. The combination of linear and non-linear function is also introduced in trend removal. For the comparison, monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful especially for the time series that has stable characteristics and has rather strong seasonal trend and also the case that has non-linear trend. The effectiveness of this method should be examined in various cases.

• Journal of the Korean Data and Information Science Society
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• 제27권4호
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• pp.1059-1066
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• 2016

In this paper we propose a robust version of varying coefficient models, which is based on the regularized regression with L1 regularization. We use the iteratively reweighted least squares procedure to solve L1 regularized objective function of varying coefficient model in locally weighted regression form. It provides the efficient computation of coefficient function estimates and the variable selection for given value of smoothing variable. We present the generalized cross validation function and Akaike information type criterion for the model selection. Applications of the proposed model are illustrated through the artificial examples and the real example of predicting the effect of the input variables and the smoothing variable on the output.

• 응용통계연구
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• 제25권6호
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• pp.1049-1058
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• 2012

Nonparametric methods are often used as an alternative to parametric methods to estimate density function and regression function. In this paper we consider improved methods to select the Bezier points in Bezier curve smoothing that is shown to have the same asymptotic properties as the kernel methods. We show that the proposed methods are better than the existing methods through numerical studies.

• Industrial Engineering and Management Systems
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• 제12권3호
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• pp.244-253
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• 2013

In industries, shipping is an important issue in improving the forecasting accuracy of sales. This paper introduces a hybrid method and plural methods are compared. Focusing the equation of exponential smoothing method (ESM) that is equivalent to (1, 1) order autoregressive-moving-average (ARMA) model equation, a new method of estimating the smoothing constant in ESM had been proposed previously by us which satisfies minimum variance of forecasting error. Generally, the smoothing constant is selected arbitrarily. However, this paper utilizes the above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate the smoothing constant. Thus, theoretical solution is derived in a simple way and it may be utilized in various fields. Furthermore, combining the trend removing method with this method, we aim to improve forecasting accuracy. This method is executed in the following method. Trend removing by the combination of linear and 2nd order nonlinear function and 3rd order nonlinear function is executed to the original production data of two kinds of bread. Genetic algorithm is utilized to search the optimal weight for the weighting parameters of linear and nonlinear function. For comparison, the monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non-monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful for the time series that has various trend characteristics and has rather strong seasonal trend. The effectiveness of this method should be examined in various cases.

• Journal of Advanced Marine Engineering and Technology
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• 제31권4호
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• pp.433-440
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• 2007

In this paper a new dynamoelectric winch system is introduced which is widely applied in shipping. building, architecture and so on. Generally in the winch system the squirrel cage induction motor is used as prime mover and line voltage is directly applied to the induction motor during operation. So it is difficult to obtain the smoothing revolution. because of variation of the weight of cargo and system operating method. Based on above reasons, the switched reluctance motor (SRM) is proposed to replace the induction motor because of more reliable mechanical structure, better traction characteristic and higher efficiency compared to induction motor. And in order to solve smoothing revolution problem, instantaneous torque control method based on torque sharing function (TSF) is used. Finally the validity of the proposed method is verified through the simulation and experimental results.