• Journal of KIEE
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• 제11권1호
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• pp.1-7
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• 2001

Various methods for blind source separation (BSS) are based on independent component analysis (ICA) which can be viewed as a nonlinear extension of principal component analysis (PCA). Most existing ICA methods require certain nonlinear functions (which leads to higher-order statistics) depending on the probability distributions of sources, whereas PCA is a linear learning method based on second-order statistics. In this paper we show that the PCA can be applied to the task of BBS, provided that source are spatially uncorrelated but temporally correlated. Since the resulting method is based on only second-order statistics, it avoids the nonlinear function and is able to separate mixtures of several colored Gaussian sources, in contrast to the conventional ICA methods.

• 전기학회논문지
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• 제57권8호
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• pp.1454-1463
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• 2008

Blind source separation by independent component analysis (ICA) has applied in signal processing, telecommunication, and image processing to recover unknown original source signals from mutually independent observation signals. Neural networks are learned to estimate the original signals by unsupervised learning algorithm. Because the outputs of the neural networks which yield original source signals are mutually independent, then mutual information is zero. This is equivalent to minimizing the Kullback-Leibler convergence between probability density function and the corresponding factorial distribution of the output in neural networks. In this paper, we present a learning algorithm using information theory and higher order statistics to solve problem of blind source separation. For computer simulation two deterministic signals and a Gaussian noise are used as original source signals. We also test the proposed algorithm by applying it to several discrete images.

• Communications for Statistical Applications and Methods
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• 제7권3호
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• pp.955-958
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• 2000

In this paper, it will be shown that if the distribution function F of X is increasing (decresign) failure rate, then the spacings are engatively( Positively) dependent. Some numberical exmamples are illustrated.

• Communications for Statistical Applications and Methods
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• 제7권3호
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• pp.687-698
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• 2000

An identification method is proposed in order to detect more than one outlying cells in multi-way contingency tables. The iterative proportional fitting method is applied to get expected values of several suspected outlying cells. Since the proposed method uses minimal sufficient statistics under quasi log-linear models, expected counts of outlying cells could be estimated under any hierarchical log-linear models. This method is an extension of the backwards-stepping method of Simonoff(1988) and requires les iteration to identify outlying cells.

• 응용통계연구
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• 제25권5호
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• pp.821-827
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• 2012

In this study, we propose a new nonparametric test procedure for the multivariate data. In order to accommodate the generalized alternatives for the multivariate case, we construct test statistics via-values with some useful combining functions. Then we illustrate our procedure with an example and compare efficiency among the combining functions through a simulation study. Finally we discuss some interesting features related with the new nonparametric test as concluding remarks.

• 대한수학회보
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• 제45권1호
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• pp.75-93
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• 2008

The rate of convergence of the distribution of order statistics to the corresponding extreme-value distribution may be characterized by the uniform and total variation metrics. de Haan and Resnick [4] derived the convergence rate when the second order generalized regularly varying function has second order derivatives. In this paper, based on the properties of the generalized regular variation and the second order generalized variation and characterized by uniform and total variation metrics, the convergence rates of the distribution of the largest order statistic are obtained under weaker conditions.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.859-871
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• 2003

In this paper we introduce some adaptive M-estimators using selector statistics to estimate the slope of regression model under the symmetric and continuous underlying error distributions. This selector statistics is based on the residuals after the preliminary fit L$_1$ (least absolute estimator) and the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying symmetric distributions in the location model. If we use L$_1$ as a preliminary fit to get residuals, we find the asymptotic distribution of sample quantiles of residual are slightly different from that of sample quantiles in the location model. If we use the functions of sample quantiles of residuals as selector statistics, we find the suitable quantile points of residual based on maximizing the asymptotic distance index to discriminate distributions under consideration. In Monte Carlo study, this adaptive M-estimation method using selector statistics works pretty good in wide range of underlying error distributions.

• 디지털산업정보학회논문지
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• 제17권4호
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• pp.133-146
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• 2021

In the field of food and drug, the role of the Ministry of Food and Drug Safety is becoming more important for national and public safety as well as national development and improvement of public welfare. Food and drug statistics are being used to determine the priorities and directions of policy for the promotion of public health and the development of the health industry. This study focuses on statistics from the MFDS. Through the analysis of the MFDS's statistics, the current status of the MFDS's production statistics was identified, and the survey of utilization and satisfaction of the MFDS's statistics was conducted on food and drug experts who actually use the statistics of the MFDS. In order to identify problems of the MFDS statistics, environmental factors affecting the MFDS statistics were derived, and the priorities of improvement tasks for its statistics were identified using AHP and IPA. In addition, the current situation of the statistical system, which serve as the basic coordinate for the establishment and execution of domestic food and drug policies, was identified and implications were provided.

• 수산경영론집
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• 제48권2호
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• pp.19-32
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• 2017

The purpose of this study is to identify problems and suggest improvements of estimating procedures and item of fisheries supply-demand statistics served as a basis for the fisheries supply-demand policies. Korea Rural Economic Institute(KREI) and Ministry of Oceans and Fisheries(MOF) respectively publish the fisheries supply-demand statistics. But the reliability of data is low as the statistics of these two organizations are limited and show discrepancy in the numbers. It is therefore difficult to use them as the basic data for policies. Also, an accurate data aggregation is difficult due to following problems in the items of statistics. 1) Problems in estimating route sales and non-route sales of production, 2) adequacy of fishery product yield rate compared to raw material in the fisheries import/export sector, 3) selection of target companies for understand stocks and survey scope of fish species, 4) applying'0'to non-edible product demand etc. In order to develop the fisheries industry as a future growth industry, it is necessary to establish the accurate fisheries supply-demand policy as the instability of fisheries supply and demand is increasing. To do this, statistical reliability has to be improved. The improvements proposed in this study should be implemented considering urgency. First of all, an exhaustive analysis of stock statistics and conversion rates of raw material yield in the fisheries import/export sector should be conducted. In the medium term and the long term, transferring production statistics to MOF and surveys on the use demand of non-food product and the level of reduced and discarded seafood products should be carried out in consecutive order.

• 응용통계연구
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• 제31권3호
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• pp.409-416
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• 2018

재무 분야에서는 주식 시장에서 투자자들의 행동형태에 대해 많은 연구가 있었다. 본 연구에서는 주식 투자자들의 주식에 대한 관심 정도가 주식의 수익률에 영향을 미치는 효과를 나타내는 관심효과(attention effect)를 실제 자료분석을 통해 검증하고자 한다. 이러한 효과를 실증적인 자료분석으로부터 검증하기는 쉽지 않았는데, 그 이유는 관심정도를 객관화하여 측정하는 것이 어려운 문제였기 때문이다. 그런데, Da 등 (2011)는 구글 검색창에서의 검색빈도로 관심정도를 측정하고, 이를 바탕으로 미국 주식시장에서의 관심효과를 검증하였다. 본 논문에서는 다음커뮤니케이션이 운영하는 주식 채틱방에서 주식종목에 대한 언급횟수에 대한 순위를 통해 관심정도를 측정하고, 언급횟수에 대한 순위가 높을수록 주식의 수익률이 높아졌다고 할 수 있는지 한국 주식시장에서의 관심효과를 검증하고자 하였다. 이를 위해, 관심효과를 순서제약이 있는 가설로 표현하고, 이에 대한 가능도비 검정절차를 제안하였으며 실제 데이터에 적용해 보았다.