Research map / Probabilistic and scientific modeling / Causal discovery
Vector Causal Inference between Two Groups of Variables
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use 2G-VecCI.Full instead of 2G-VecCI.PC | Vector causal direction inference · Simulated linear and nonlinear data | correct causal direction recovery | Helped |
| Use groupwise conditional-dependence edge densities rather than Vanilla-PC microstructure discovery | Vector causal direction inference · Simulated data, generally | causal direction recovery | Helped |
| Use Vanilla-PC rather than the proposed groupwise methods | Vector causal direction inference · Simulated data with small groups and sparse interactions | causal direction recovery | Helped |
| Increase interaction effect size and interaction density | 2G-VecCI methods · Simulated data | causal direction recovery | Helped |
| Increase within-group edge density | 2G-VecCI methods · Simulated data | causal direction recovery | Hurt |
| Use extremely sparse interactions | 2G-VecCI.Full · Quadratic interactions, group sizes 15 and 25 | correct causal direction recovery | Hurt |
| Apply 2G-VecCI.Full to ENSO and British Columbia temperatures | 2G-VecCI.Full · ENSO 3.4–British Columbia coarse grainings | inference direction: μ = 0.031; 0.59 correct, 0.27 wrong | Helped |
| Apply 2G-VecCI.PC rather than 2G-VecCI.Full | ENSO–British Columbia temperature inference · ENSO 3.4–British Columbia coarse grainings | inference decisiveness: μ = 0.001; σ = 0.019 | Hurt |
| Use the Trace Method rather than 2G-VecCI methods | Linear group interactions with Gaussian noise · Simulated data | runtime | Helped |
| Use 2G-VecCI.Full rather than Vanilla-PC | Linear causal direction inference · Groups of size 30, 100 samples, increasing interaction density | correct causal direction recovery | Helped |
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