Abstract. A numerical technique for the reconstruction of diffusion processes (diffusions, in short) from data is presented. The drift and diffusion coefficients of the generator of the diffusion are found by minimizing an object function which measures the difference between the eigenspectrum of the operator and a reference eigenspectrum. The reference spectrum can be obtained, in discretized ...

Path coupling is a useful technique for simplifying the analysis of a coupling of a Markov chain. Rather than defining and analysing the coupling on every pair in Ω ×Ω , where Ω is the state space of the Markov chain, analysis is done on a smaller set S ⊆Ω ×Ω . If the coefficient of contraction β is strictly less than one, no further analysis is needed in order to show rapid mixing. However, if...

This study aims to develop a new one-vendor multiple-buyers integrated inventory model. We believe that our proposed model can forecast the demand of all buyers in coming future by using data have already existed and minimize total cost-for both vendors. In recent days, Markov chain approach has played one critical methods forecasting Supply Chain Management (SCM) field. The this is analysis sp...

In this paper we will treat input selection for a radial basis function (RBF) like classifier within a Bayesian framework. We approximate the a-posteriori distribution over both model coefficients and input subsets by samples drawn with Gibbs updates and reversible jump moves. Using some public datasets, we compare the classification accuracy of the method with a conventional ARD scheme. These ...

6 Over the last decades, the α-stable distribution has proved to be a very efficient 7 model for impulsive data. In this paper, we propose an extension of stable distribu8 tions, namely mixture of α-stable distributions to model multimodal, skewed and 9 impulsive data. A fully Bayesian framework is presented for the estimation of the 10 stable density parameters and the mixture parameters. As o...