Process monitoring using profile data remains an important and challenging problem in various manufacturing industries. Motivated by application case of motherboard testing processes, we develop a novel modeling framework for heterogeneous multivariate profiles. In this framework, graphical model is constructed to depict the complicated relationship among channels. Then channels can be reduced ...

Many phenomena are correlated and spatially dependent. In addition, some of them ordinal discrete responses. Thus, a model is needed to capture the interactions multivariate outcomes spatial dependences. Following Smith LeSage (2004) Jeliazkov et al. (2008), this study proposes new algorithm for ordered probit (MSOP) address need. applying model, parameters calculated using Bayesian inference b...

In forecasting real time environmental factors, large data is needed to analyse the pattern behind values. Air pollution a major threat towards developing countries and it proliferating every year. Many methods in series prediction deep learning models estimate severity of air pollution. Each independent variable contributing necessary trend that particular locality. This approach selects multi...