Overview of the methodology

Brief introduction to the time distance methodology

Sicherl Time distance and MDG leaflet.pdf (260.73 KB 18.06.2007 22:38)   

Concept and definition of S-time-distance and S-time-step 

 S-TIME-DISTANCE AS A SPECIAL CATEGORY OF TIME DISTANCE.doc (45.50 KB 16.06.2007 09:18)
 

S-time-distance as a new generic statistical measure for analysis and visualization of time series data

The novel generic statistical measure S-time-distance yields a radical new view of time series datasets that has been left unexplored by the present state-of-the-art. It represents an additional view, complementing rather than replacing the existing statistical measures of time series analysis. It is theoretically universal, intuitively understandable, and relevant to many problems and applications. Thus it can be usefully applied as an important analytical and presentation tool at macro and micro levels to a wide variety of substantive fields.

S-time-distance as a new generic statistical measure.pdf (313.35 KB 11.11.2007 03:00)

Presentation example: Time Distance – New Generic Approach for Analysis and Presentation of Time Related Data 

Presented at the Time Distance Analysis conference at the George Washington University, October 25, 2005, Washington D.C. 

Measuring progress of societies

 Sicherl Measuring Progress of Societies Radenci 2006.pdf (574.46 KB)

Recent time distance bibliography (from 2007 to 2002) 

 Recent time distance bibliography 2007-2002.pdf (134.22 KB 19.06.2007 22:23)

Time Distance – New Generic Approach for Analysis and Visualisation of Time Related Data

The art of handling different views of data is crucial for discovering the relevant patterns and for providing a broader framework for policy analysis. The new generic time distance approach (with associated novel statistical measure S-time-distance) offers a new view of data that is exceptionally easy to understand and communicate, and it allows for developing and exploring new hypotheses and perspectives.



Presented at the Pascal Workshop, Complex objects visualization 2005, University of Primorska, Koper, November 16, 2005
 

Recent time distance bibliography 2007 and 2006.doc (36.50 KB)

Last Updated ( Sunday, 11 November 2007 )