• Title/Summary/Keyword: Random measures

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LIMIT THEOREM FOR ASSOCIATED RANDOM MEASURES

  • Ru, Dae-Hee
    • Journal of applied mathematics & informatics
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    • v.3 no.1
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    • pp.89-100
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    • 1996
  • In this paper we investigate a limit theorem for a non-statioary d-parameter array of associated random variables applying the criterion of the tightness condition in Donsker, M[1951]. Our re-sults imply an extension to the nonstatioary case of Convergence of Probability Measure of billingsley. P[1986]. and analogous results for the d-dimensional associated random measure. These results are also applied to show a new limit theorem for Poisson cluster random mea-sures.

Joint HGLM approach for repeated measures and survival data

  • Ha, Il Do
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.4
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    • pp.1083-1090
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    • 2016
  • In clinical studies, different types of outcomes (e.g. repeated measures data and time-to-event data) for the same subject tend to be observed, and these data can be correlated. For example, a response variable of interest can be measured repeatedly over time on the same subject and at the same time, an event time representing a terminating event is also obtained. Joint modelling using a shared random effect is useful for analyzing these data. Inferences based on marginal likelihood may involve the evaluation of analytically intractable integrations over the random-effect distributions. In this paper we propose a joint HGLM approach for analyzing such outcomes using the HGLM (hierarchical generalized linear model) method based on h-likelihood (i.e. hierarchical likelihood), which avoids these integration itself. The proposed method has been demonstrated using various numerical studies.

PACKING DIMENSION OF MEASURES ON A RANDOM CANTOR SET

  • Baek, In-Soo
    • Journal of the Korean Mathematical Society
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    • v.41 no.5
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    • pp.933-944
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    • 2004
  • Packing dimension of a set is an upper bound for the packing dimensions of measures on the set. Recently the packing dimension of statistically self-similar Cantor set, which has uniform distributions for contraction ratios, was shown to be its Hausdorff dimension. We study the method to find an upper bound of packing dimensions and the upper Renyi dimensions of measures on a statistically quasi-self-similar Cantor set (its packing dimension is still unknown) which has non-uniform distributions of contraction ratios. As results, in some statistically quasi-self-similar Cantor set we show that every probability measure on it has its subset of full measure whose packing dimension is also its Hausdorff dimension almost surely and it has its subset of full measure whose packing dimension is also its Hausdorff dimension almost surely for almost all probability measure on it.

Multicollinarity in Logistic Regression

  • Jong-Han lee;Myung-Hoe Huh
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.303-309
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    • 1995
  • Many measures to detect multicollinearity in linear regression have been proposed in statistics and numerical analysis literature. Among them, condition number and variance inflation factor(VIF) are most popular. In this study, we give new interpretations of condition number and VIF in linear regression, using geometry on the explanatory space. In the same line, we derive natural measures of condition number and VIF for logistic regression. These computer intensive measures can be easily extended to evaluate multicollinearity in generalized linear models.

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Random Access Method of the Wibro System

  • Lee, Kang-Won
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.1A
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    • pp.49-57
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    • 2011
  • Random access method for Wibro system is proposed using the Bayesian Technique, which can estimate the number of bandwidth request messages in a frame only based on the number of successful slots. The performance measures such as the maximum average throughput, the mean delay time and the collision ratio are investigated to evaluate the performance of the proposed method. The proposed method shows better performance than the binary exponential backoff algorithm used currently.

BMAP/M/N/O Queueing System in Random Environments

  • Kim, Che-Soong
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2007.04a
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    • pp.461-465
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    • 2007
  • The BMAP/M/N/O queueing system operating in Markovian random environment is investigated. The stationary distribution of the system is calculated. Loss probability and other performance measures are calculated. Numerical experiments which show the necessity of taking into account the influence of random environment and correlation in input flow are presented.

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Structural Aspects in the Theory of Random Walk

  • Heyer, H.
    • Journal of the Korean Statistical Society
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    • v.11 no.2
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    • pp.118-130
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    • 1982
  • Random walks as specia Markov stochastic processes have received particular attention in recent years. Not only the applicability of the theory already developed but also its extension within the frame work of probability measures on algebraic-topological structures such as semigroups, groups and linear spaces became a new challenge for research work in the field. At the same time new insights into classical problems were obtained which in various cases lead to a more efficient presentation of the subject. Consequently the teaching of random walks at all levels should profit from the recent development.

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Noisy Band Removal Using Band Correlation in Hyperspectral lmages

  • Huan, Nguyen Van;Kim, Hak-Il
    • Korean Journal of Remote Sensing
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    • v.25 no.3
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    • pp.263-270
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    • 2009
  • Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

Choquet expected values of fuzzy number-valued random variables and their applications (퍼지수치 확률변수의 쇼케이 기댓값과 그 응용)

  • Jang LeeChae;Kim TaeKyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.1
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    • pp.98-103
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    • 2005
  • In this paper, we consider interval number-valued random variables and fuzzy number-valued random variables and discuss Choquet integrals of them. Using these properties, we define the Choquet expected value of fuzzy number-valued random variables which is a natural generalization of the Lebesgue expected value of fuzzy random variables. Furthermore, we discuss some application of them.