A number of approaches have been developed for analyzing incident clearance time data and investigating the effects of different explanatory variables on clearance time. Among these methods, hazard-based duration models (i.e., proportional hazard and accelerated failure time models) have been extensively used. The finite mixture model is an alternative approach in survival data analysis, and of...

In a Bayesian mixture model it is not necessary a priori to limit the number of components to be finite. In this paper an infinite Gaussian mixture model is presented which neatly sidesteps the difficult problem of finding the “right” number of mixture components. Inference in the model is done using an efficient parameter-free Markov Chain that relies entirely on Gibbs sampling.

effect of water gas shift reaction (co+h2o=co2+h2) on wustite reduction has been investigated by a transient, non-isothermal mathematical model based on grain model. in this model, wustite porous pellet is reduced using syngas, namely a mixture of hydrogen, carbon monoxide, carbon dioxide and water vapor. for this purpose, governing equations containing continuity equation of species and energy...

This study presents a finite element (FE) micromechanical modelling approach for the simulation of linear and damage-coupled viscoelastic behaviour of asphalt mixture. Asphalt mixture is a composite material of graded aggregates bound with mastic (asphalt and fine aggregates). The microstructural model of asphalt mixture incorporates an equivalent lattice network structure whereby intergranular...

We propose a Bayesian method for variable selection in the finite mixture model of linear regressions. The model assumes that the observations come from a heterogeneous population which is a mixture of a finite number of sub-populations. Within each sub-population, the response variable can be explained by a linear regression on the predictor variables. So the whole data set can be modeled by a...

experiments were carried out to observe the influence of loading type on concrete beam specimens. beam specimens made of similar concrete mixture with the same geometry were tested under three point static loading and low velocity drop weight impact loading. load – displacement behavior, absorbed energy dissipation capacity, stiffnesses, failure modes of beam specimens were obtained and discuss...

Finite mixture models are a popular tool for modelling unobserved heterogeneity. As these models are in general very complex, it is essential to have suitable methods for model diagnostics which allow e.g. to check for model identifiability, model fit and possible model restrictions. In this paper we propose to use the parametric bootstrap for model diagnostics and to visualize the bootstrap re...

The Semi-Naive Bayesian network (SNB) classifier, a probabilistic model with an assumption of conditional independence among the combined attributes, shows a good performance in classification tasks. However, the traditional SNBs can only combine two attributes into a combined attribute. This inflexibility together with its strong independency assumption may generate inaccurate distributions fo...

The use of Riemannian manifolds and their statistics has recently gained popularity in a wide range of applications involving non-linear data modeling. For instance, they have been used to model shape changes in the brain [1] and human motion [3]. In this work we tackle the problem of approximating the Probability Density Function (PDF) of a potentially large dataset that lies on a known Rieman...