|
|||||
|
|
A coherence-based approach for the pattern recognition of time series |
|
| Authors: | Elizabeth Ann Maharaj Pierpaolo D’Urso |
| Institution: | a Department of Econometrics and Business Statistics, Monash University-Caulfield Campus, 900 Dandenong Road, Caulfield East, Melbourne, Victoria 3145, Australia b Dipartimento di Teoria Economica e Metodi Quantitativi per le Scelte Politiche, Sapienza Universita’ di Roma, P.za Aldo Moro, 5-00185, Rome, Italy |
| Abstract: | A pattern recognition approach based on the frequency domain measure of squared coherence is a useful approach to identify linearly related groupings of time series over different periods of time. It is considered in an application to identify similar patterns of the yearly rates of change in the Gross Domestic Product (GDP) of twenty two highly developed countries in an econophysics context. The approach is also tested in simulation studies using linearly related time series, and it is shown to have a very good success rate of correct pattern matching. |
| Keywords: | Linearly related time series Gross Domestic Product Squared coherence measure Pattern recognition of time series Partitioning Around Medoids Econophysics |
| 本文献已被 ScienceDirect 等数据库收录！ | |