• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1023-1032
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• 2007

We introduce the statistical system of the Commonwelth Independence State(CIS) countries located in the Central Asia. At present, the level of the national statistics production system of Korean National Statistical Office(NSO) is very high and locate on just behind Japan among all asian countries, and they are also trying to reach the statistics quality level upto the advanced developed countries in the world. To have the optimal Statistics production processing, we must understand the methodologies parts as well as the aspect of the macro statistics that can be applied to the country#s economic plan. Like the history is repeated, it is valuable to look at the development history of statistical system of other countries one century ago. We study the relationship among CIS countries along with the history of Russian statistics development. It will be helpful to look and understand the statistical system of CIS countries including Russia to use their statistics for international comparison study.

• Applied Biological Chemistry
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• v.20 no.3
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• pp.270-278
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• 1977

In case of sensory evaluation with multi-samples and long-period, in spite of using method with good sensitivity, quality differences among samples could net be detected well because of panel's fatigue and tiredness. So new method to reduce panel's sense of psychological and physiological responsibility, "Trio Paired Comparison", is designed, and New Modified Scheffe's Method 2 as the statistical method for a test of "Trio Paired Comparison" is proposed. And also in this paper problems and countermeasures in applicating "Trio Paired Comparison" are considered.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.119-125
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• 1999

This paper gives an overview of the various approaches to designing statistical pattern recognition scheme based on Bayes discrimination rule and the artificial neural networks for rotating machine condition classification. Concerning to Bayes discrimination rule, this paper contains the linear discrimination rule applied to classification into several multivariate normal distributions with common covariance matrices, the quadratic discrimination rule under different covariance matrices. Also we discribes k-nearest neighbor method to directly estimate a posterior probability of each class. Five features are extracted in time domain vibration signals. Employing these five features, statistical pattern classifier and neural networks have been established to detect defects on rotating machine. Four different cases of rotation machine were observed. The effects of k number and neural networks structures on monitoring performance have also been investigated. For the comparison of diagnosis performance of these two method, their recognition success rates are calculated form the test data. The result of experiment which classifies the rotating machine conditions using each method presents that the neural networks shows the highest recognition rate.

• Journal of the Korean Professional Engineers Association
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• v.29 no.2
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• pp.71-79
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• 1996

This paper evaluates the clustering performance of a neural network and a statistical method. Algorithms which are used in this paper are the GLVQ(Generalized Loaming vector Quantization) for a neural method and the k -means algorithm for a statistical clustering method. For comparison of two methods, we calculate the Rand's c statistics. As a result, the mean of c value obtained with the GLVQ is higher than that obtained with the k -means algorithm, while standard deviation of c value is lower. Experimental data sets were the Fisher's IRIS data and patterns extracted from handwritten numerals.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.899-911
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• 2000

In this paper, we reviewed thirteen methods for finding confidence intervals for he mean of poisson distribution. Bootstrap confidence intervals are also introduced. Two bootstrap confidence intervals are compared with the other existing eleven confidence intervals by using Monte Carlo simulation with respect to the average coverage probability of Woodroofe and Jhun (1989).

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.125-134
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• 2003

Standard estimation methods for linear mixed models are sensitive to influential observations. However, tools and concepts for linear mixed model diagnostics are rudimentary until now and research is heavily demanded in linear mixed models. In this paper, we consider two diagnostics to evaluate the effects of individual observations in the estimation of fixed effects for linear mixed models. Those are Cook's distance and COVRATIO. Results of our limited simulation study suggest that the Cook's distance is not good statistical quantity in linear mixed models. Also calibration point for COVRATIO seems to be quite conservative.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.31-38
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• 2003

A simple method is proposed to detect the number of change points and test the location and size of multiple change points with jump discontinuities in an otherwise smooth regression model. The proposed estimators are based on a local linear regression fit by the comparison of left and right one-side kernel smoother. Our proposed methodology is explained and applied to real data and simulated data.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.369-378
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• 2006

This Study focuses on the binary forecast of occurrence of heavy snow in Honam area based on the MOS(model output statistic) method. For our study daily amount of snow cover at 17 stations during the cold season (November to March) in 2001 to 2005 and Corresponding 45 RDAPS outputs are used. Logistic regression model and neural networks are applied to predict the probability of occurrence of Heavy snow. Based on the distribution of estimated probabilities, optimal thresholds are determined via true shill score. According to the results of comparison the logistic regression model is recommended.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.335-346
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• 2015

The purpose of this study is to compare not only network influence of individual coauthor but also the types and properties of two coauthor networks of Communications for Statistical Applications and Methods and the Korean Journal of Applied Statistics which are published by the Korean Statistical Society using social network analysis.As the result of two network structure comparison, density, inclusiveness, reciprocity and clustering coefficient which represent the type of coauthor networks show almost similar values and the Korean Journal of Applied Statistics has bigger values in average degree, average distance and diameter because it has more nodes than Communications for Statistical Applications and Methods. Finally two journals have very similar type of coauthor network. In the comparison of network centrality of two coauthor networks, closeness centrality and betweenness centrality of the Korean Journal of Applied Statistics are bigger than those of Communications for Statistical Applications and Methods at the statistical significance level 0.05. The coauthor network of the Korean Journal of Applied Statistics has faster information delivery and stronger betweenness than that of Communications for Statistical Applications.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.49-56
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• 1999

This paper present a study on the application of sound pressure and vibration signals to detect the presence of defects in a rolling element bearing using a statistical analysis method. The well established statistical parameters such as the crest factor and the distribution of moments including kurtosis and skewless are utilized in this study. In addition, other statistical parameters derived from the beta distribution function are also used. A comparison study on the performance of the different types of parameter used is also performed. The statistical analysis is used because of its simplicity and quick computation. Under ideal conditions, the statistical method can be used to identify the different types of defect present in the bearing. In addition, the results also reveal that there is no significant advantages in using the beta function parameters when compared to using kurtosis and the crest factor for detecting and identifying defects in rolling element bearings from both sound and vibration signals.