Algorithms and programs of dynamic mixture estimation. Unified approach to different types of components (Q2012677)

The book presents and discusses dynamic mixture models and their use in estimation and prediction. It starts with the presentation of single linear regression, categorical and state-space models and their use in estimation and prediction. It then formulates the general dynamic mixture model and proceeds to its use in different estimation and prediction problems involving different components. Algorithms along with their software implementation in Scilab, an open source programming environment, are also provided for the examined problems. Different experiments are presented in order to demonstrate the features and potentials of the discussed models and their algorithmic implementations. Mixture models have applications in several domains such as industry, engineering, social science, medicine, transportation etc. The book therefore can be of interest to researchers and PhD students in many diverse fields.