Markov chain Monte Carlo (MCMC) methods for Bayesian computation are mostly used when the dominating measure is the Lebesgue measure, the counting measure, or a product of these. Many Bayesian problems give rise to distributions that are not dominated by the Lebesgue measure or the counting measure alone. In this article we introduce a simple framework for using MCMC algorithms in Bayesian comp...

cantharidin is one of the most well- known compounds which has ever been fascinating in medicine due to its effects on human and domestic animals. it is produced naturally by beetles of family meloidae and oedemeridae, however a considerable spectra of other insects sequestered it too. cantharidin along with the other analogue, palasonin, which has a methyl group less than it, found in the hemo...

let h be a finite dimensional complex hilbert space, b(h)+ be the set of all positive semi-definite operators on h and phi is a (not necessarily linear) unital map of b(h) + preserving the entropy-gibbs transformation. then there exists either a unitary or an anti-unitary operator u on h such that phi(a) = uau* for any b(h) +. thermodynamics, a branch of physics that is concerned with the study...

1 Probabilistic approach in image analysis. The basic idea of probabilistic approach in image analysis, see e.g. [1, 2], was to rewrite an image processing procedure in the language of statistical physics using concepts of statistical ensembles, equilibrium and non-equilibrium dynamics. Under this view, images are considered as configurations of a Gibbs field. The implicit assumption behind the...

This paper proposes a novel model estimationmethod, which uses nested Gibbs sampling to develop amixture-of-mixture model to represent the distribution of the model’s components with a mixture model. This model is suitable for analyzing multilevel data comprising frame-wise observations, such as videos and acoustic signals, which are composed of frame-wise observations. Deterministic procedures...