greencredit {bnRep} | R Documentation |
greencredit Bayesian Network
Description
The coupling relationships and influence mechanisms of green credit and energy-environment-economy under China's goal of carbon neutrality.
Format
A discrete Bayesian network nvestigate the coupling relationships and influence mechanisms of green credit and 3E system. Probabilities were given within the referenced paper (missing distributions were set as uniform). The vertices are:
- ECS
Energy consumption structure (High, Medium, Low);
- EI
Energy intensity (High, Medium, Low);
- EPI
Environment (High, Medium, Low);
- GCI
Interest expense proportion (High, Medium, Low);
- GDP
Economy sharing (High, Medium, Low);
- IS
Green economy (High, Medium, Low);
- OU
Economy opening up (High, Medium, Low);
- PEC
Per capita energy consumption (High, Medium, Low);
- TP
Economy innovation (High, Medium, Low);
- UR
Economy coordination (High, Medium, Low);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Chai, J., Wang, Y., Hu, Y., Zhang, X., & Zhang, X. (2023). The Coupling Relationships and Influence Mechanisms of Green Credit and Energy-Environment-Economy Under China's Goal of Carbon Neutrality. Journal of Systems Science and Complexity, 36(1), 360-374.