• Journal of the Korean Statistical Society
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• v.34 no.1
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• pp.35-38
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• 2005

A single, tractable, special case of the problem of continuous mixtures of beta distributions over their parameters is considered. This is the uniform mixture of generalized arc-sine distributions which, curiously, turns out to be linked by transformation to the Cauchy distribution.

• International Journal of Reliability and Applications
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• v.10 no.2
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• pp.63-79
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• 2009

A new bivariate linear failure rate distribution is introduced through a shock model. It is proved that the marginal distributions of this new bivariate distribution are linear failure rate distributions. The joint moment generating function of the bivariate distribution is derived. Mixtures of bivariate linear failure rate distributions are also discussed. Application to a real data is given.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.109-130
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• 2018

Several measures of multivariate skewness for scale mixtures of skew-normal distributions are derived. As a special case, those of multivariate skew-t distribution are considered in detail. Furthermore, the similarities, differences, and behavior of these measures are explored for cases of some specific members of the multivariate skew-normal and skew-t distributions using a simulation study. Since some measures are vectors, it is better to take all measures in the same scale when comparing them. In order to attain such a set of comparable indices, the sample version is considered for each of the skewness measures that are taken as test statistics for the hypothesis of t distribution against skew-t distribution. An application is reported for the data set consisting of 71 total glycerol and magnesium contents in Grignolino wine.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.349-355
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• 2007

In this paper we study some important properties of the bivariate generalized hypergeometric probability (BGHP) distribution by establishing the existence of all the moments of the distribution and by deriving recurrence relations for raw moments. It is shown that certain mixtures of BGHP distributions are again BGHP distributions and a limiting case of the distribution is considered.

• Journal of Industrial Technology
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• v.11
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• pp.3-16
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• 1991

The lattice-fluid theory are adopted for modeling the phese equilibria in supercritical fluids, In order to investigate effects of the nonrandom distribution of holes in mixtures on the phase equilibria, the equation of state and the chemical potential of the binary miture are formulated with taking into account nonrandomness of holes distributions in the fluid mixture. The relations of phase equilibria formulated in this work are tested through predictions of solubility of heavy solids in supercritical fluids and predictions of high pressure phase equilibria of binary mixtures. Results obtained exhibit that the lattice fluid model with assumptions of nonrandomness of hole distributions is successful in quantatively mideling the phase equilibria of mixtures of molecules of dissimilar sizes, specifically solids-supercritical fluid mixtures.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.81-91
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• 2014

This study derives the characteristic functions of (multivariate/generalized) t distributions without contour integration. We extended Hursts method (1995) to (multivariate/generalized) t distributions based on the principle of randomization and mixtures. The derivation methods are relatively straightforward and are appropriate for graduate level statistics theory courses.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1071-1083
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• 2005

By estimating probability distributions of the good solutions in the current population, some researchers try to find the optimal solution more efficiently. Particularly, finite mixtures of distributions have a very useful role in dealing with complex problems. However, it is difficult to choose the number of components in the mixture models and merge superior partial solutions represented by each component. In this paper, we propose a new continuous evolutionary optimization algorithm with distribution estimation by variational Bayesian mixtures of factor analyzers. This technique can estimate the number of mixtures automatically and combine good sub-solutions by sampling new individuals with the latent variables. In a comparison with two probabilistic model-based evolutionary algorithms, the proposed scheme achieves superior performance on the traditional benchmark function optimization. We also successfully estimate the parameters of S-system for the dynamic modeling of biochemical networks.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.867-873
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• 2001

In this paper we propose a family of skew- f distributions. The family is derived by a scale mixtures of skew-normal distributions introduced by Azzalini (1985) and Henze (1986). The salient features of the family are mathematical tractability and strict inclusion of the normal law. Further it includes a shape parameter, to some extent, controls the index of skewness. Necessary theory involved in deriving the family of distributions is provided and main properties of the family are also studied.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.704-705
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• 2006

Discrete element analysis is used to map various log-normal particle size distributions into measures of the in-sphere pore size distribution. Combinations evaluated range from monosized spheres to include bimodal mixtures and various log-normal distributions. The latter proves most useful in providing a mapping of one distribution into the other (knowing the particle size distribution we want to predict the pore size distribution). Such metrics show predictions where the presence of large pores is anticipated that need to be avoided to ensure high sintered properties.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.10
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• pp.942-951
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• 2004

This paper presents the results of a theoretical study of the effect of radiation during free convective laminar film boiling for methanol/water binary mixtures on an isothermal vertical wall at atmospheric pressure. With the well-known boundary layer theory as a basis, a theoretical model has been formulated into consideration for mass diffusion at liquid phase. The equations are numerically solved by a similarity method to investigate the effects of radiation emissivity on the surface with various parameters such as wall superheat and composition of more volatile component at liquid phase far from the wall. From the results, the distributions of the physical quantifies are investigated in both phases. New correlations are proposed to predict the heat transfer coefficient of binary mixtures. It is shown that the proposed correlations are in good agreement with numerical results and with Bromley's correlation within maximum $11\%$ errors. It is also found that as the wall superheat is increased, radiation effect becomes more important.