Characterizing Interdependencies of Multiple Time Series : Theory and Applications

Characterizing Interdependencies of Multiple Time Series : Theory and Applications /

This book introduces academic researchers and professionals to the basic concepts and methods for characterizing interdependencies of multiple time series in the frequency domain. Detecting causal directions between a pair of time series and the extent of their effects, as well as testing the non ex...

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Bibliographic Details
Main Authors: Hosoya, Yuzo (Author), Kinoshita, Ryo (Author), Oya, Kosuke (Author), Takimoto, Taro (Author)
Format: Electronic eBook
Language:English
Published: Singapore : Springer Singapore : Imprint: Springer, 2017.
Series:SpringerBriefs in statistics.
Subjects:
Statistics.
Statistical Theory and Methods.
Statistics and Computing/Statistics Programs.
Statistics for Business/Economics/Mathematical Finance/Insurance.
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Statistics for Life Sciences, Medicine, Health Sciences.
Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
Online Access:Connect to this title online
Table of Contents:
  • 1: Introduction to statistical causal analysis
  •  2: Measures of one-way effect, reciprocity and association.- 3: Partial measures of interdependence.- 4: Inference based on the vector autoregressive and moving average model
  • 5: Inference on change in causality measures.- 6: Simulation performance of estimation methods.- 7: Empirical analysis of macroeconomic series
  • 8: Empirical analysis of change in causality measures.- 9: Conclusion.- Appendix.- References.- Index.

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