Statistical analysis of time series with scaling indices
Statistical techniques based on scaling indices are applied to detect and investigate patterns in empirically given time series. The key idea is to use the distribution of scaling indices obtained from a delay representation of the empirical time series to distinguish between random and non-random...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2000-01-01
|
| Series: | Discrete Dynamics in Nature and Society |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1155/S1026022600000595 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832550036694630400 |
|---|---|
| author | Harald Atmnaspacher Werner Ehm Herbert Scheingraber Gerda Wiedenmann |
| author_facet | Harald Atmnaspacher Werner Ehm Herbert Scheingraber Gerda Wiedenmann |
| author_sort | Harald Atmnaspacher |
| collection | DOAJ |
| description | Statistical techniques based on scaling indices are applied to detect and investigate patterns in empirically given time series. The key idea is to use the distribution of scaling indices obtained from a delay representation of the empirical time series to distinguish
between random and non-random components. Statistical tests for this purpose are designed and applied to specific examples. It is shown that a selection of subseries by scaling indices can significantly enhance the signal-to-noise ratio as compared to that of the total time series. |
| format | Article |
| id | doaj-art-e22936af714248ec8606c0d364b2692d |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2000-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-e22936af714248ec8606c0d364b2692d2025-02-03T06:07:58ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2000-01-015429730910.1155/S1026022600000595Statistical analysis of time series with scaling indicesHarald Atmnaspacher0Werner Ehm1Herbert Scheingraber2Gerda Wiedenmann3lnstitut für Grenzgebiete der Psychologie, Wilhelmstr. 3a, Freiburg D-79098, Germanylnstitut für Grenzgebiete der Psychologie, Wilhelmstr. 3a, Freiburg D-79098, GermanyMax-Planck-Institut für extraterrestrische Physik, Giessenbachstr., Garching D-85740, GermanyMax-Planck-Institut für extraterrestrische Physik, Giessenbachstr., Garching D-85740, GermanyStatistical techniques based on scaling indices are applied to detect and investigate patterns in empirically given time series. The key idea is to use the distribution of scaling indices obtained from a delay representation of the empirical time series to distinguish between random and non-random components. Statistical tests for this purpose are designed and applied to specific examples. It is shown that a selection of subseries by scaling indices can significantly enhance the signal-to-noise ratio as compared to that of the total time series.http://dx.doi.org/10.1155/S1026022600000595Time series analysis; Pattern detection; Scaling indices. |
| spellingShingle | Harald Atmnaspacher Werner Ehm Herbert Scheingraber Gerda Wiedenmann Statistical analysis of time series with scaling indices Discrete Dynamics in Nature and Society Time series analysis; Pattern detection; Scaling indices. |
| title | Statistical analysis of time series with scaling indices |
| title_full | Statistical analysis of time series with scaling indices |
| title_fullStr | Statistical analysis of time series with scaling indices |
| title_full_unstemmed | Statistical analysis of time series with scaling indices |
| title_short | Statistical analysis of time series with scaling indices |
| title_sort | statistical analysis of time series with scaling indices |
| topic | Time series analysis; Pattern detection; Scaling indices. |
| url | http://dx.doi.org/10.1155/S1026022600000595 |
| work_keys_str_mv | AT haraldatmnaspacher statisticalanalysisoftimeserieswithscalingindices AT wernerehm statisticalanalysisoftimeserieswithscalingindices AT herbertscheingraber statisticalanalysisoftimeserieswithscalingindices AT gerdawiedenmann statisticalanalysisoftimeserieswithscalingindices |