• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.1-18
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• 1998

Since 1960s, in which the computer graphics system first appeared, various graphical techniques have been introduced for regression diagnostics and they have been remarkably developed. In particular, animation, one of the dynamic graphical methods which Cook and Weisberg (1989) proposed helps to show the effect of adding variables or observations to a model, or removing them from a model on the regression results. We present the added variable plots (AVP) with animation, which can be used as an optical tool of understanding the affect of some variables or observations on other variables, and the detrended added-variable plots (DAVP) with animation, through which it is possible to find out whether specific variables or observations have an effect on the nonlinearity of other variables or not.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.787-797
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• 2002

Partial residual plots, augmented partial residual plots and CERES plots are basic diagnostic tools for dealing with curvature as a function of specific predictors in regression problem. However, it is known that these plots can miss a curve or show a false curve in some cases such as predictors are related each other. Dynamic display of these plots is developed and applied. Examples demonstrate that dynamic plots are useful for obtaining additional Information on the curvature.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.529-537
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• 2004

This article concerns dynamic graphical methods for visualizing a curvature in regression problem in which some predictors enter nonlinearly. A sequence of augmented partial residual plot or partial residual plot updated by the change of linear combination of two predictors are constructed. Examples demonstrate that the suggested methods can be used to reduce the dimension of explanatory variables as well as to capture a curvature.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.173-191
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• 1999

In this paper we suggest the visualized regression diagnosis tool. The tool is developed by Hangul Delphi on the basis of windows, so users can easily make use of this tool though they do not have the expert knowledge about statistics and computer. Especially, to apply this tool to teaching regression analysis or data analysis, we offer various residual plots in the tool and show the results of analysis graphically.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.193-217
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• 2001

Despite of the rich literature in discriminant analysis, this complicated subject remains much to be explored. In this article, we study the theoretical foundation that supports Fisher's linear discriminant analysis (LDA) by setting up the classification problem under the dimension reduction framework as in Li(1991) for introducing sliced inverse regression(SIR). Through the connection between SIR and LDA, our theory helps identify sources of strength and weakness in using CRIMCOORDS(Gnanadesikan 1977) as a graphical tool for displaying group separation patterns. This connection also leads to several ways of generalizing LDA for better exploration and exploitation of nonlinear data patterns.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.27-40
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• 2001

The purpose of this study is to test a multiple change point in the regression model with the passage of time, using the estimated residual variance figure suggested by Gasser, Sroka and Jennen - Steinmez (GSJS). As a result of the simulation, it is showed that there is a jump change of the estimated residual variance figure at that time of change point. The way to analyse a intuitive multiple change point through graphics is more effective and accurate than any other existing ways.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.181-191
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• 2018

Rapid development of information technology makes our environment become smarter and massive high performance computers are providing powerful computing for that. Graphics Processing Unit (GPU) as a typical high performance component is being widely used for both graphics and general-purpose applications. Although it can greatly improve computing power, it also delivers significant power consumption and need sufficient power supplies. To make high performance computing more sustainable, the important step is to measure it. Current power technologies for GPU have some drawbacks, such as they are not applicable for power estimation at the early stage. In this article, we present a novel power technology to correlate power consumption and the characteristics at the programmer perspective, and then to estimate power consumption of source program without prerunning. We conduct experiments on Nvidia's GT740 platform; the results show that our power model is more accurately than regression model and has an average error of 2.34% and the maximum error of 9.65%.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.979-986
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• 2011

A linear regression method is commonly used to analyze data because of its simplicity and applicability; however, it is well known that data may contain some outliers and influential cases that may have a harmful effect on a statistical analysis. Thus detection and examination of outliers or influential cases are important parts of data analysis. In detecting multiple outliers, masking effects usually occur and make it difficult to identify the true outliers. We propose to use dynamic plots as a method resistant to masking effect. The procedure using dynamic plots is useful to find appropriate basic sets with which a dependent outliers detection method start and detect a true outliers set. Examples are given to demonstrate the effectiveness of the suggested idea.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.193-204
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• 1998

It is quite that we have to estimate the derivative of the regression function. The Bezier curve, rarely known to statisticians, is very popular in computer graphics area. In this paper, we use nonparametric method via the Bezier curve, and apply this method to real data set. This method seems to be very easy to compute and can be easily applied to other smoothing techniques.

• Journal of the Korea Computer Graphics Society
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• v.21 no.3
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• pp.55-61
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• 2015

In this paper, we introduce a method to synthesize realistic make-up effects on input images efficiently. In particular, we focus on shading on the make-up effects due to the lighting and face curvature. By doing this, we can synthesize a wider range of effects realistically than the previous methods. To do this, the information about lighting information together with the normal vectors on all pixels over the face region in the input image. Since the previous methods that compute lighting information and normal vectors require relatively heavy computation cost, we introduce an approach to approximate lighting information using cascade pose regression process and normal vectors by transforming, rendering, and warping a standard 3D face model. The proposed method consumes much less computation time than the previous methods. In our experiment, we show the proposed approximation technique can produce naturally looking virtual make-up effects.