Uncertainty Principle for Time Series

Erscheinungsjahr 2018
ISBN: 978-1-78548-174-1
Verlag: Elsevier Science

Buch, Englisch, 150 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 375 g

Uncertainty Principle for Time Series is devoted to a "model-free� approach that bypasses most of the existing shortcomings; the proof of the existence of a "trend� is a key ingredient. Although time series is a classic object of study in many branches of applied sciences (econometrics, financial engineering, weather forecast, neurosciences, etc.), most of the existing settings are assuming the knowledge of a model and of the probabilistic nature of the uncertainties. Those assumptions are almost always impossible to fulfill. Moreover a complete and elegant mathematical treatment exists only in the case of stationary processes, which almost never occur in practice. All those points explain the difficulty of applying the existing approaches in concrete situations.

Zielgruppe

All applied scientists and experts who are utilizing time series,Mathematicians, Physicists.

Autoren/Hrsg.

Fliess, Michel

Join, Cedric

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Zeitmessung: Physikalische und Technische Aspekte
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik

Inhaltsverzeichnis

1. Nonstandard analysis of time series 2. The existence of trends of quick fluctuations 3. The uncertainty principle and a new setting for volatility 4. Causality 5. Some applications to financial engineering 6. Some applications to renewable energies

Über Autor(innen)

Fliess, Michel
Michel Fliess is a research director at Ecole Polytechnique. He obtained a PhD 1972 on Theoretical computer sciences. His research focuses on original algebraic methods in automation, estimation and identification, which have considerably advanced these disciplines

Join, Cedric
Cedric Join is an Associate Professor at CRAN, he is also a scientific expert at AL.I.E.N. with a focus on automatic control, fast estimation, real time identification, signal and image processing, model free control, financial engineering.