The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
The goal of ionet is to develop network functionalities specialized for the data generated from input-output tables.
You can install the development version of ionet from GitHub with:
btw()
: betweenness centrality measure that incorporates available node-specific auxiliary information based on strongest path.
dijkstra()
: implementation of the Dijkstra’s algorithm to find the shortest paths from the source node to all nodes in the given network.
Database | Economies | Years | Sectors |
---|---|---|---|
the National Bureau of Statistics of China | China | 2002 | 122 |
2005 | 42 | ||
2007 | 135 | ||
2010 | 41 | ||
2012 | 139 | ||
2015 | 42 | ||
2017 | 149 | ||
2017 | 42 | ||
2018 | 153 | ||
2018 | 42 | ||
2020 | 153 | ||
2020 | 42 | ||
OECD Input-Output Tables 2021 edition | China | 1995–2018 | 45 |
OECD Input-Output Tables 2021 edition | Japan | 1995–2018 | 45 |
Xiao, S., Yan, J. and Zhang, P. (2022). Incorporating auxiliary information in betweenness measure for input-output networks. Physica A: Statistical Mechanics and its Applications, 607, 128200. DOI.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.