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Usage of the Mori-Zwanzig method in time series analysis
Markus Niemann1, Thomas Laubrich, Eckehard Olbrich
1Max-Planck-Institut für Physik komplexer Systeme, Nöthnitzer Strasse 38, D-01187 Dresden, Germany. niemann@mpipks-dresden.mpg.de
The Mori-Zwanzig approach for time series analysis uses memory kernels that are difficult to interpret. Discretizing these kernels can alter their properties, raising concerns about their use in complex data analysis.
Area of Science:
- Statistical Physics
- Time Series Analysis
- Computational Mathematics
Background:
- The Mori-Zwanzig approach is a theoretical framework used in statistical physics to derive macroscopic equations from microscopic dynamics.
- Memory kernels are central to this approach, capturing the system's past influence on its present state.
- Interpreting these kernels is crucial for understanding the underlying physical processes in time series data.
Purpose of the Study:
- To investigate the interpretability of memory kernels derived from the Mori-Zwanzig formalism in time series analysis.
- To analyze the properties of a recently introduced discrete version of the memory kernel.
- To assess the applicability of the Mori-Zwanzig approach for analyzing complex time series.
Main Methods:
- Discussion of memory kernels derived from the Mori-Zwanzig approach.
- Analysis of a discrete approximation of the memory kernel.
- Rigorous mathematical analysis of the discrete kernel's properties.
- Comparison with analytically calculated memory kernels for simple time series processes.
- Examination of the relationship between finite Mori-Zwanzig kernel models and Autoregressive Moving Average (ARMA) models.
Main Results:
- Memory kernels from the Mori-Zwanzig approach are not easily interpretable, even for analytical models.
- Discretization of the memory kernel can lead to properties significantly different from its continuous form.
- Features of simple time series processes are often not detectable in their corresponding discrete memory kernels.
- Finite Mori-Zwanzig kernel models represent a specific subset of ARMA models.
Conclusions:
- The interpretability challenges of Mori-Zwanzig memory kernels, especially in their discrete forms, limit their practical application.
- The findings cast doubt on the reliability of the Mori-Zwanzig approach for analyzing complex time series data due to obscured properties.
- Further research is needed to develop more interpretable methods for time series analysis using Mori-Zwanzig formalism or alternative approaches.
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