A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual ...

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual ...

This paper presents a Bayesian hierarchical model to estimate the spatial-temporal photovoltaic potential in residential areas. The proposed model offers a probabilistic approach that uses technical criteria of planners ...

We investigate the possibilities of New Physics affecting the Standard Model (SM) Higgs sector. An effective Lagrangian with dimension-six operators is used to capture the effect of New Physics. We carry out a global ...

Clustering algorithms typically group points based on some similarity criterion, but without reference to an underlying random process to make clustering algorithms rigorously predictive. In fact, there exists a probabilistic ...

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual ...

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming ...

In this paper, a supervisor system, able to diagnose different types of faults during the operation of a proton exchange membrane fuel cell is introduced. The diagnosis is developed by applying Bayesian networks, which ...