Abstract
This short paper proves inequalities that restrict the magnitudes of the partial correlations in star-shaped structures in Gaussian graphical models. These inequalities have to be satisfied by distributions that are used for generating simulated data to test structure-learning algorithms, but methods that have been used to create such distributions do not always ensure that they are. The inequalities are also noteworthy because stars are common and meaningful in real-world networks.
| Original language | English |
|---|---|
| Pages (from-to) | 5990-5996 |
| Number of pages | 7 |
| Journal | Communications in Statistics - Theory and Methods |
| Volume | 45 |
| Issue number | 20 |
| Early online date | 8 Feb 2016 |
| DOIs | |
| Publication status | Published - Feb 2016 |
Keywords
- Gaussian graphical model
- Partial correlation
- Star
- Hub
- Sylvester's criterion
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