Statistical Modeling and Applications

In an era defined by the seamless integration of data and sophisticated analytical and modeling techniques, the quest for advanced statistical modeling and methodologies has never been more pertinent. This book entitled "Statistical Modeling and Applications: Multivariate, Heavy-Tailed, Skewed Distributions, Mixture and Neural-Network Modeling, Volume 2", represents a concerted effort to bridge the gap between theoretical advancements and practical applications in the realm of Statistical Science, namely in the area of Statistical Modeling. It also aims to present a wide range of emerging topics in mathematical and statistical modeling written by a group of distinguished researchers from top-tier universities and research institutes in order to offer broader opportunities to foster and stimulate further collaborations in the areas of mathematics and statistics.

The book has eleven chapters, divided in two Parts, with Part I comprising five chapters dealing with the application of Multivariate Analysis techniques and multivariate distributions to a set of different situations, and Part II consisting of six chapters which address the modeling of a number of interesting phenomena through the use of Heavy-Tailed, Skewed, Circular-Linear and Mixture Distributions and also Neural Networks.