• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1892-1902
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• 2016

NIST SP 800-90B is developed to evaluate the security of entropy sources. As SP 800-90B was updated to Second Draft, Estimators with predictors were added at Non-IID track. Though the predictors are known as detecting periodic property of noise sources, periodic properties which are detected by predictor are not clearly known. In this paper, we experiment to find properties of predictors. Once, by experiments we have a result that the min-entropy of Non-IID noise sources is generally determined by tests except for estimators with predictors. And then through presenting various experimental results for clarifying periodic properties detected by predictor, we experimentally analyze on its meaning and role of predictor estimation.

• Environmental and Resource Economics Review
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• v.26 no.4
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• pp.613-639
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• 2017

A Maximum Entropy (ME) Model and an Analytical Model are analyzed in assessing Kapenta stock in Lake Kariba. The ME model estimates a Maximum Sustainable Yield (MSY) of 25,372 tons and a corresponding effort of 109,731 fishing nights suggesting overcapacity in the lake at current effort level. The model estimates a declining stock from 1988 to 2009. The Analytical Model estimates an Acceptable Biological Catch (ABC) annually and a corresponding fishing mortality (F) of 1.210/year which is higher than the prevailing fishing mortality of 0.927/year. The ME and Analytical Models estimate a similar biomass in the reference year 1982 confirming that both models are applicable to the stock. The ME model estimates annual biomass which has been gradually declining until less than one third of maximum biomass (156,047 tons) in 1988. It implies that the stock has been overexploited due to yieldings over the level of ABC compared to variations in annual catch, even if the recent prevailing catch levels were not up to the level of MSY. In comparison, the Analytical Model provides a more conservative value of ABC compared to the MSY value estimated by the ME model. Conservative management policies should be taken to reduce the aggregate amount of annual catch employing the total allowable catch system and effort reduction program.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.131-143
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• 1994

Under the asymmetric losses (entropy loss and Stein loss), we find the classes of Bayes and empiricla Bayes estimates for estimating the Poisson means when the distributin of means are believed a priori. Following the idea of Efron and Morris (1973), we have a computer simulation to compute a relative savings loss of proposed estimates as compared to the classical estimates.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.527-540
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• 2010

Rule-based classification analysis is widely used for massive datamining because it is easy to understand and its algorithm is uncomplicated. In this classification analysis, majority vote of rules or weighted combination of rules using their supports are frequently used in order to combine rules. We propose a method to combine rules by using the multinomial distribution in this paper. Iterative proportional fitting algorithm is used to estimate the multinomial distribution which maximizes entropy constrained on rules' support. Simulation experiments show that this method can compete with other well known classification models in the case of two similar populations.

• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.139-148
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• 2015

The purpose of image fusion is to combine the relevant information from a set of images into a single image, where the resultant fused image will be more informative and complete than any of the input images. Image fusion techniques can improve the quality and increase the application of these data important applications of the fusion of images include medical imaging, remote sensing, and robotics. In this paper, we suggest a new method to generate a fusion image using the close relation of image features obtained through maximum entropy threshold and mutual information. This method represents a good image registration in case of using a blurring image than other image fusion methods.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.2
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• pp.39-46
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• 2000

Recent]y van Es (1992) and Correa (1995) proposed an estimator of entropy. In this paper, we proposed the goodness of fit test statistics for exponentiality based on Vasicek's estimator and Correa's estimator of Kullback-Leibier Information. And we compare the power of the proposed test statistics with Kolmogorov-Sminov, Kuiper, Cramer von Mises, Watson, Andersen-Darling and Finkelstein and Schefer statistics.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.611-622
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• 2013

Mudholkar and Tian (2002) proposed an entropy-based test of fit for the inverse Gaussian distribution; however, the test can be applied to only the composite hypothesis of the inverse Gaussian distribution with an unknown location parameter. In this paper, we propose an entropy-based goodness-of-fit test for an inverse Gaussian distribution that can be applied to the composite hypothesis of the inverse Gaussian distribution as well as the simple hypothesis of the inverse Gaussian distribution with a specified location parameter. The proposed test is based on the probability integration transformation. The critical values of the test statistic estimated by simulations are presented in a tabular form. A simulation study is performed to compare the proposed test under some selected alternatives with Mudholkar and Tian (2002)'s test in terms of power. The results show that the proposed test has better power than the previous entropy-based test.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.148-148
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• 2011

Riemann 문제는 천수방정식과 같은 쌍곡선형 방정식과 단일한 도약에 의해 불연속인 어떤 점의 좌 우에서 상수인 자료로 구성되는 초기치 문제로서 그 해법은 Godunov 방법과 같이 정확해에 의하면 정확 Riemann 해법, 근사 기법에 의하면 근사 Riemann 해법으로 불린다. 지금까지 이용되는 근사 Riemann 해법으로는 1981년에 P. L. Roe가 제안한 Roe의 선형화 기법과 1983년에 A. Harten, P. D. Lax, 그리고 B. van Leer가 제안한 HLL 기법의 수정 기법들이다. 최대 및 최소 파속만 고려하는 것으로 알려진 HLL 기법은 1988년에 B. Einfeldt의 제안에 의해 두 파속의 결정에서 Roe의 선형화 기법에 따른 고유치와 비교하는 것으로 수정되었다(HLLE 기법). 또한, 1994년에 E. F. Toro 등은 접촉파를 고려하기 위해 선형화된 지배방정식의 정확해로부터 중앙 파속을 고려하는 기법을 제안하였고, 이를 HLLC 기법으로 불렀다. 2002년에 T. Linde는 중앙 파속을 평가하기 위해 일반화된(수학적) 엔트로피 함수를 도입하였으며, van Leer는 이를 HLLL 기법으로 불렀다. 이 기법에서는 접촉파의 평가를 위해 보존변수에 대한 일반화된 엔트로피 함수로부터 중앙 파속이 유도되며, 이것과 특성 속도의 비교를 통해 최대 및 최소 파속이 결정된다. 따라서 이 기법에서는 모든 파속이 초기치로부터 결정되므로 HLLE 기법과 달리 Roe의 선형화 기법과 완전히 결별되고 HLLC 기법과 달리 정확해에 의존되지 않는 점에서 HLLL 기법은 모태인 HLL 기법의 온전한 계승으로 볼 수 있다. HLLL 기법은 여러 분야에 적용된 바 있으나, 수공학 분야에 적용된 사례는 알려진 바 없다. 이는 천수방정식에 대한 (물리적) 엔트로피 함수가 명확하지 않기 때문인 것으로 보인다. 이 연구에서는 보존변수로부터 정의되는 총 에너지를 일반화된 엔트로피 함수로 간주하여 모형을 구성하고, 정확해가 알려진 1차원 문제에 대해 적용성을 검토하였다. 정확해가 알려진 경우에 대해 모의한 결과, 1차 정도 수치해의 한계에도 불구하고, HLLL 기법의 결과는 대체로 정확해와 잘 일치하였으며 그 외의 HLL-형 기법의 그것에 비해 우수한 것으로 나타났다. 특히, 물이 빠져 바닥이 드러나는 상태에 대한 접촉 파속의 추정에서 Riemann 불변량을 이용하는 HLLC 기법에 비해 물이 빠지는 전선을 더 정확하게 포착하는 HLLL 기법의 결과는 매우 고무적이었다.

• Journal of the Korean association of regional geographers
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• v.21 no.1
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• pp.21-38
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• 2015

This study attempts to estimate the complementarity between 21 cities in the Korean Southeastern Region using data on the network time distance and the volume of flow between the cities. Four types of flows recognized are people, commodities, information and finance. The first two types of flows are thought to be made on the transportation network while the last two are on the communication network. For the purpose of the study, the expected volumes of flows between cities are first estimated using the gravity-based regression and doubly-constrained entropy maximization models. These baseline volumes are then subtracted from the observed volumes of flows (of people and commodities) or the estimated volumes of flows (of information and finance) in order to identify positive differences or complementarities. The result shows that these four types of complementarity flows form distinctive urban networks in terms of spatial pattern and urban hierarchy. This suggests that more customized strategies to different types of complementarity are recommended to properly address the issues related to network infrastructure provision in the pursuit of the network city model in the region.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.301-312
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• 2008

Mutual information is a measure of association of explanatory variable for predicting target variable. It is used for variable ranking and variable subset selection. This study is about the Sample-spacing approach which can be used for the estimation of mutual information from data consisting of continuous explanation variables and categorical target variable without estimating a joint probability density function. The results of Monte-Carlo simulation and experiments with real-world data show that m = 1 is preferable in using Sample-spacing.