Time Series and Networks Analysis

This textbook provides students with a hands-on introduction to time series analysis. Readers will learn the potential of the methods but also benefit from a step-by-step guide to apply them on simple data, as well as applications in real science in domains such as physics, environmental science, physics of fluids, simulation analysis etc. The authors emphasize application of the techniques and modern methodologies for time series analysis, using examples to demonstrate techniques introduced, including detailed, step-by-step solutions. Octave and Matlab are used as the computational environment for the applications, since the readers can find programs easily for many applications. The commands are clearly explained and the files are provided in the text and online.

Offers textbook coverage of applied time series analysis Introduces theory as necessary, while emphasizing application of the techniques and modern methodologies for time series analysis Uses applied examples to demonstrate techniques introduced, including detailed, step-by-step solutions

Autorentext

Dr. h. Karakasidis is currently Professor of Applied Physics at the School of Sciences of the University of Thessaly, Greece, after serving for 15 years at the Department of Civil Engineering in the same University. Before joining the University of Thessaly, Dr. Karakasidis has worked for the French Atomic Energy Commission at the Nuclear Research Center of Saclay and Ecole Polytechnique (Paris). His primary research interests are: Computational Materials Science, atomistic and multiscale modeling and simulation, nanoscience and nanotechnology, statistical physics and system dynamics, time series analysis and machine learning. He received his B.S. in Physics at the Aristotle University of Thessaloniki, Greece (1989), his M.S. (1991) and his PhD in Physics (1995) from University Pierre et Marie Curie (Paris 6), France. He has also served as Visiting Professor in the University of Cyprus and Visiting researcher in the University Joseph Fourier Grenoble, France. He has been involved in several research programs funded by the European Union and the Greek Government. Dr. Karakasidis is the author of nearly 100 publications in international peer reviewed scientific journals, and 100 international and national conference papers and presentations. He has supervised several PhD students in the area of materials modeling and time series analysis. He has served as a reviewer in international scientific journals. He has taught several courses in Numeral Analysis, Numerical Modeling, Econophysics, Time series analysis and data analysis both in undergraduate and graduate level. He is co-author textbooks in Numerical Analysis and Academic Righting (in Greek) that are employed in many University Departments in Greece.

Dr. Avraam Charakopoulos is an engineer at Hellenic Tactical Air Force, and Postdoctoral Research Associate in the Department of Physics, School of Sciences, University of Thessaly, Greece. His research topics include analysis of dynamical systems in interdisciplinary research fields, linear and non-linear analysis of time series, computational statistics, complex network science analysis of univariate and multivariate time series and currently focused on machine learning and network data science. Some of his recent research characterizes the effects of complex network time series analysis with applications on computational and field data. From August 2010 to July 2015, he has been a PhD student in Civil Engineering at the University of Thessaly, Greece, where he obtained his PhD degree. He received a Bachelor's Degree from 1996 to 2000 in Engineering at the Hellenic Air Force Academy, his Master's Degree from 2005 to 2007 in Computational Engineering at the University of Thessaly. He is also active in the scientific field where he is author of publications in international peer-reviewed scientific journals and acts as reviewer in international scientific journals. His academic experience includes teaching Numerical Analysis Based on Matlab/Octave as Adjunct Lecturer at the Department of Civil Engineering of University of Thessaly).

Inhalt

Introduction.- Time series statistics.- Time domain analysis.- Correlation and causality.- Clustering time series.- Nonlinear analysis.- Complex network time series.- Topological properties of networks.- Introduction to machine learning.- Unsupervised / Supervised method.- Machine learning and networks.- Analyzing large simulation results.- Examples of Experimental Data.- Examples of Field Measurement Data.- Examples of Finance Data.