• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.909-917
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• 2003

Although many classification models have been used to classify binary data, none of the classification models dominates all varying circumstances depending on the number of variables and the size of data(Asparoukhov and Krzanowski (2001)). This paper proposes a classification model which uses information on marginal distributions of sub-variables and its maximum entropy distribution. Classification experiments by using simulation are discussed.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.695-705
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• 2003

In this article, we propose a regression and correlation analysis via dynamic graphs and implement them in Java Web Start. For the polynomial relations between dependent and independent variables, dynamic graphics are implemented for both polynomial regression and spline estimates for an instant model selection. The results include basic statistics. They are available both as a web-based service and an application.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.375-382
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• 1999

Linear-by-linear association models are commonly used to analyze ordered categorical data. To fit these models appropriate scores need to be chosen. In this paper we perform sensitivity analyses in two-way contingency tables to investigate the effect of scores on goodness-of-fits and on tests of significance. In addition we show that the best score which yields the best fit of data can be selected based on the sensitivity analysis results.

• 한국데이터정보과학회:학술대회논문집
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• 2003.05a
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• pp.159-170
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• 2003

This Paper analyzed simultaneous activities of the time use survey by Korea National Statistical Office to use data mining‘s association rule. The survey of National Statistical Office in 1999 considered general analysis for simultaneous activities. But if we use the association rule, we can found the ratio of particular activities at the same time. And we found the probability that another activities practise if we act one particular activity. Using this association rule of data mining we can do more developed and analytical sociological study.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.116.3-116
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• 2001

A diagnosis methodology for thickness quality in hot finishing mill is proposed based on multivariate statistical analysis. The thickness of hot strip is a key quality factor that is measured by x-ray thickness gauge. Currently, the thickness quality is guaranteed by upper and lower limit of thickness deviation from target thickness. But if any over-limit is occurred, there is no in-line method to identify the causes. In this paper, many parameters are extracted from the thickness deviation signal such as mean deviation(top, middle, tail), rms deviation(top, middle, tail) and peak deviation(top, middle, tail) as time domain parameters ...

• The Journal of Korean Medicine
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• v.22 no.2
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• pp.75-83
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• 2001

In order to investigate anti-cancer effect of Cremastrae Appendiculatae Tuber, this experiment was performed, in vitro. The results are as follows: 1. The MIT assay demonstrated that cell viability was decreased by Cremastrae Appendiculatae Tuber without statistical significance 2. The Apoptosis assay demonstated that apoptosis was induced by Cremastrae Appendiculatae Tuber without statistical significance 3. In quantitative RT-PCR analysis, there were no remarkable changes in expression levels of apoptosis-related genes, Bcl- 2, Bax, P53.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.865-868
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• 1999

In this paper, indoor propagation characteristics are analyzed for various environments such as corridors, walls and corners. In order to present the statistical model for indoor environments the loss factors of each case are obtained by linear regression analysis method with the function of logarithmic distance between transmitter and receiver.

• International Journal of Quality Innovation
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• v.1 no.1
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• pp.97-105
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• 2000

In this paper, a two-section method for measuring is introduced and the variation sources of measurement process are analysed. Measuring is a special process in general process. Various variation source must be firstly decomposed so that the statistical distribution law of measuring process can be established, and then implement monitoring control of the measuring process. A special method to obtain the measuring variation is discussed, and a monitoring control technique for measuring process is studied based statistical distribution. Towards the end, we briefly introduce software design for the analysis and control of a measurement process.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.151-156
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• 2003

Variable selection algorithm for principal component analysis using penalized likelihood method is proposed. We will adopt a probabilistic principal component idea to utilize likelihood function for the problem and use HARD penalty function to force coefficients of any irrelevant variables for each component to zero. Consistency and sparsity of coefficient estimates will be provided with results of small simulated and illustrative real examples.

• Korean Management Science Review
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• v.11 no.1
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• pp.117-128
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• 1994

This paper describes a case study on the analysis of RAM(Reliability, Availability, and Maintainability) factors obtained from the Endurance-Test for a military full-tracked armored vehicle. In analysing RAM factors of the vehicle we used such a statistical technique as method of Maximum-Likelihood for estimating parameters.