Empirical Mode Decomposition Applied to Afghanistan Violence Data: Comparison with Multiplicative Seasonal Decomposition
Abstract
The empirical mode decomposition (EMD) is applied to violence data from Afghanistan between 2006 and2012. Several key behaviours are identified at distinct time scales ranging from days, through weeks to months,through months to a year, and finally spanning multiple years. The identified behaviour was compared to thetraditionally-used multiplicative seasonal decomposition. Unlike seasonal decomposition, the EMD does not make aprioriassumptions about periodicity, and thus was better able to identify the multi-year cycle, without the skewed trendin the vicinity of turning points of the near-annual cycle. In addition, the EMD isolated shorter time scales with distinctstatistical behaviour thus enriching the opportunities for analysis of drivers at different scales. Overall, the EMDdemonstrated its usefulness and applicability, enhancing the analysis of violence data. The next step is to apply it toother types of time-series in the defence context to establish it firmly as a part of the defence analysis toolbox.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 2014
- Accession Number
- AD1017606
Entities
People
- James A. Wanliss
- Peter Dobias
Organizations
- Defence Research and Development Canada