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The goal of ionet is to develop network functionalities specialized for the data generated from input-output tables.

Installation

You can install the development version of ionet from GitHub with:

# install.packages("devtools")
devtools::install_github("Carol-seven/ionet")

Function

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.

Data | Input-Output Tables

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.