This paper introduces a novel class of Bayesian models for multivariate time series analysis based on a synthesis of dynamic linear models and graphical models. The synthesis uses sparse graphical modelling ideas to introduce structured, conditional independence relationships in the time-varying, cross-sectional covariance matrices of multiple time series. We define this new class of models and...

The aim of this paper is to compare Bayesian network classifiers to the k-NN classifier based on a subset of features. This subset is established by means of sequential feature selection methods. Experimental results show that Bayesian network classifiers more often achieve a better classification rate on different data sets than selective k-NN classifiers. The k-NN classifier performs well in ...

In this article, an overview of Bayesian methods for sequential simulation from posterior distributions nonlinear and non-Gaussian dynamic systems is presented. The focus mainly laid on Monte Carlo methods, which are based particle representations probability densities can be seamlessly generalized to any state-space representation. Within context, a unified framework the various Particle Filte...

Accelerated life testing (ALT) is typically used to assess the reliability of material's lifetime under desired stress levels. Recent advances in material engineering have made a variety alternatives readily available. To identify most reliable setting with efficient experimental design, sequential test planning strategy preferred. guarantee tractable statistical mechanism for information colle...