2023/10/01 by Nils Antary, Martin H. Trauth, Norbert Marwan · 1 voice
Computer Science · Earth and Planetary Sciences · Economics, Econometrics and Finance · Mathematics · #Algorithm #Artificial intelligence #Bilinear interpolation #Complex Systems and Time Series Analysis #Computer science #Computer vision #Diagonal #Geology and Paleoclimatology Research #Geometry #Interpolation (computer graphics) #Mathematics #Multivariate interpolation #Nonlinear system #Physics #Preprocessor #Recurrence plot #Recurrence quantification analysis #Sampling (signal processing) #Spline interpolation #Statistics #Time Series Analysis and Forecasting #Trilinear interpolation
paper · doi:10.1063/5.0167413
openalex publication_date 2023/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
The recurrence plot and the recurrence quantification analysis (RQA) are well-established methods for the analysis of data from complex systems. They provide important insights into the nature of the dynamics, periodicity, regime changes, and many more. These methods are used in different fields of research, such as finance, engineering, life, and earth science. To use them, the data have usually to be uniformly sampled, posing difficulties in investigations that provide non-uniformly sampled data, as typical in medical data (e.g., heart-beat based measurements), paleoclimate archives (such as sediment cores or stalagmites), or astrophysics (supernova or pulsar observations). One frequently used solution is interpolation to generate uniform time series. However, this preprocessing step can introduce bias to the RQA measures, particularly those that rely on the diagonal or vertical line structure in the recurrence plot. Using prototypical model systems, we systematically analyze differences in the RQA measure average diagonal line length for data with different sampling and interpolation. For real data, we show that the course of this measure strongly depends on the choice of the sampling rate for interpolation. Furthermore, we suggest a correction scheme, which is capable of correcting the bias introduced by the prepossessing step if the interpolation ratio is an integer.