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Table 8 Comparison of proposed method with statistical method

From: Mining precise cause and effect rules in large time series data of socio-economic indicators

Dataset Indicators relationships Extracted rules Statistical methods
Proposed method Granger causality Bayesian network
Synthetic-1 (I1–I6) Binary I1 → I3
Many to one (I2, I4) → I5   
Transitive I1 → I3 → I6  
Cyclic I1 ←→ I3   
Synthetic-2 (I1–I10) Binary I1 → I7, I2 → I7, I7 → I2, I1 → I3, I7 → I8
Many to one (I6, I9) → I7   
Transitive I1 → I7 → I8  
Cyclic I2 ←→ I7   
WTO Binary Chemicals → Textiles Chemicals → OTE
Many to one (OTE, Textiles) → EDOE   
Transitive IS → OM → ICEC  
Cyclic OM ←→ IS   
IMF Binary GGR → VEG
Many to one (GGR, GNS) → TI   
Transitive GDP → VIG → TI  
Cyclic CAB ←→ VEGS   
World Bank data Binary CP → ARME
Many to one (FDI, FR) → CPI   
Transitive AR → AG → CO2  
Cyclic GDP ←→ CY