Open AccessAnalysis of Information Society Indicators with Time Distance Methodology
Author(s) -
Pavle Sicherl
Publication year - 2005
Publication title -
cit. journal of computing and information technology/journal of computing and information technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.169
H-Index - 27
eISSN - 1846-3908
pISSN - 1330-1136
DOI - 10.2498/cit.2005.04.06
Subject(s) - computer science , measure (data warehouse) , typology , per capita , time series , statistical analysis , the internet , statistics , econometrics , data science , data mining , world wide web , mathematics , machine learning , population , demography , archaeology , sociology , history
A novel generic statistical measure S-time-distance complementing existing methods of analysis of time series data is briefly presented. The application to indicator analysis shows that the gap between compared units may be very different when compared with commonly used static measures and with time distance measure, leading to a special typology of indicators. Analysis of indicators like PC per 100 inhabitants and Internet users per capita will show the empirical results for EU countries