Trends in Mathematical, Information and Data Sciences

ISBN-13: 9783031041396 / Angielski / Miękka / 2023

Opis

This book involves ideas/results from the topics of mathematical, information, and data sciences, in connection with the main research interests of Professor Pardo that can be summarized as Information Theory with Applications to Statistical Inference. This book is a tribute to Professor Leandro Pardo, who has chaired the Department of Statistics and OR of the Complutense University in Madrid, and he has been also President of the Spanish Society of Statistics and Operations Research.  In this way, the contributions have been structured into three parts, which often overlap to a greater or lesser extent, namely

• Trends in Mathematical Sciences (Part I)
• Trends in Information Sciences (Part II)
• Trends in Data Sciences (Part III)

The contributions gathered in this book have offered either new developments from a theoretical and/or computational and/or applied point of view, or reviews of recent literature of outstanding developments. They have been applied through nice examples in climatology, chemistry, economics, engineering, geology, health sciences, physics, pandemics, and socioeconomic indicators. Consequently, the intended audience of this book is mainly statisticians, mathematicians, computer scientists, and so on, but users of these disciplines as well as experts in the involved applications may certainly find this book a very interesting read.

Spis treści

Using taxes to manage energy resources related to stock pollutants: resource cartel vs importers.- A new Shapley value-based rule for distributing delay costs in stochastic projects.- Variogram model selection.- On first passage times in discrete skeletons and uniformized versions of a continuous-time Markov chain.- A numerical approximation of a two-dimensional atherosclerosis model.- Generalized models for binary and ordinal responses.- Approximations of δ -record probabilities in i.i.d. and trend models.- The Relative Strength Index (RSI) to monitor GDP variations: Comparing regions or countries from a new perspective.