New Understanding and Insights from Time-Series Data Based on Two Generic Measures: S-Time-Distance and S-Time-Step
Time distance is an innovative approach for looking at time-series data. Expressed in time units, the approach is easy to understand and provides a useful complement to existing methods. The time distance approach compares time series in the horizontal dimension, i.e. for a given level of the variab...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Paris
OECD Publishing
2011
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| Schriftenreihe: | OECD Statistics Working Papers
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| Schlagworte: | |
| Online-Zugang: | kostenfrei |
| Zusammenfassung: | Time distance is an innovative approach for looking at time-series data. Expressed in time units, the approach is easy to understand and provides a useful complement to existing methods. The time distance approach compares time series in the horizontal dimension, i.e. for a given level of the variable, based on two generic statistical measures: S-time-distance and S-time-step. These measures are based on a time matrix that summarises information over many units and years and that provides a first-level visualization tool. The paper also introduces the concept of the 'overall degree of disparity', defined as proximity in the indicator space as well as in time, arguing that this concept has the potential to bring new understanding in economics, management, research and statistics |
| Beschreibung: | 1 Online-Ressource (35 Seiten) 21 x 29.7cm |
| DOI: | 10.1787/5kg1zpzzl1tg-en |
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| spelling | Sicherl, Pavle Verfasser aut New Understanding and Insights from Time-Series Data Based on Two Generic Measures S-Time-Distance and S-Time-Step Pavle Sicherl Paris OECD Publishing 2011 1 Online-Ressource (35 Seiten) 21 x 29.7cm txt rdacontent c rdamedia cr rdacarrier OECD Statistics Working Papers Time distance is an innovative approach for looking at time-series data. Expressed in time units, the approach is easy to understand and provides a useful complement to existing methods. The time distance approach compares time series in the horizontal dimension, i.e. for a given level of the variable, based on two generic statistical measures: S-time-distance and S-time-step. These measures are based on a time matrix that summarises information over many units and years and that provides a first-level visualization tool. The paper also introduces the concept of the 'overall degree of disparity', defined as proximity in the indicator space as well as in time, arguing that this concept has the potential to bring new understanding in economics, management, research and statistics Economics https://doi.org/10.1787/5kg1zpzzl1tg-en Verlag kostenfrei Volltext |
| spellingShingle | Sicherl, Pavle New Understanding and Insights from Time-Series Data Based on Two Generic Measures S-Time-Distance and S-Time-Step Economics |
| title | New Understanding and Insights from Time-Series Data Based on Two Generic Measures S-Time-Distance and S-Time-Step |
| title_auth | New Understanding and Insights from Time-Series Data Based on Two Generic Measures S-Time-Distance and S-Time-Step |
| title_exact_search | New Understanding and Insights from Time-Series Data Based on Two Generic Measures S-Time-Distance and S-Time-Step |
| title_exact_search_txtP | New Understanding and Insights from Time-Series Data Based on Two Generic Measures S-Time-Distance and S-Time-Step |
| title_full | New Understanding and Insights from Time-Series Data Based on Two Generic Measures S-Time-Distance and S-Time-Step Pavle Sicherl |
| title_fullStr | New Understanding and Insights from Time-Series Data Based on Two Generic Measures S-Time-Distance and S-Time-Step Pavle Sicherl |
| title_full_unstemmed | New Understanding and Insights from Time-Series Data Based on Two Generic Measures S-Time-Distance and S-Time-Step Pavle Sicherl |
| title_short | New Understanding and Insights from Time-Series Data Based on Two Generic Measures |
| title_sort | new understanding and insights from time series data based on two generic measures s time distance and s time step |
| title_sub | S-Time-Distance and S-Time-Step |
| topic | Economics |
| topic_facet | Economics |
| url | https://doi.org/10.1787/5kg1zpzzl1tg-en |
| work_keys_str_mv | AT sicherlpavle newunderstandingandinsightsfromtimeseriesdatabasedontwogenericmeasuresstimedistanceandstimestep |