Research map / Probabilistic and scientific modeling / Causal discovery
Discovering Potential Correlations via Hypercontractivity
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the hypercontractivity coefficient instead of conventional correlation estimators | Potential-correlation detection · Synthetic functional associations | detection power at fixed false-positive rate | Helped |
| Use the hypercontractivity estimator for cubic associations | Potential-correlation detection · Cubic synthetic association | detection power | Hurt |
| Place the dominant independent samples to the left rather than adjacent to the rare correlated region | HC estimator · Cubic synthetic association | detection power | Helped |
| Use the HC estimator rather than competing correlation measures | Gene pathway recovery · Single-cell gene-expression time series, regular and antigen-exposed T-cells | trend recovery accuracy | Helped |
| Use the HC estimator to detect dependence in a rare subgroup | WHO national indicators · WHO country-indicator pairs | hidden potential-correlation detection | Helped |
| Allow a single outlier to contribute to the estimate | HC estimator · WHO indicators and synthetic outlier examples | estimated hypercontractivity: 0.99; 0.04; 0.17 | Mixed |
| Remove the United States outlier | HC estimate for broadband subscribers and private health expenditure · WHO country indicators | hypercontractivity | Hurt |
| Remove the second largest-country outlier after removing China | HC estimate for male colon and rectum cancer deaths and health expenditure · WHO country indicators | hypercontractivity: 0.17 | Hurt |
| Remove Norway and Iceland from the samples | HC estimate for energy use and hydroelectricity consumption · WHO country indicators | hypercontractivity: 0.49 | Hurt |
| Estimate the dependence in the reverse direction | Hypercontractivity coefficient · Rare/dominant dependence scenario | potential-correlation coefficient | Hurt |
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