Man pages for gRapHD
Efficient Selection of Undirected Graphical Models for High-Dimensional Datasets
| adjMat | Adjacency matrix |
| calcStat | Pairwise weights |
| ccoeff | Clustering coefficient |
| chStat | Internal use |
| CI.test | Test of conditional independence |
| convData | Converts dataset |
| Degree | Degree |
| DFS | Depth-first search |
| dsCont | Test dataset |
| dsDiscr | Test dataset |
| dsMixed | Test dataset |
| findEd | Finds add-eligible edges |
| fit | Log-likelihood, AIC, BIC |
| gRapHD | The gRapHD package |
| gRapHD-class | Class "gRapHD" |
| jTree | Junction tree |
| MCS | Maximum cardinality search |
| minForest | Minimum forest |
| modelDim | Model's dimension |
| modelFormula | Model's formula |
| neighbourhood | Neighbourhood of a vertex |
| neighbours | Finds all direct neighbours |
| perfSets | Finds a perfect sequence |
| plot.gRapHD | Plots a gRapHD object |
| randTree | Random tree |
| rowProds | Row products |
| shortPath | Shortest path |
| sortMat | Sort matrix |
| stepb | Stepwise backward selection |
| stepw | Stepwise forward selection |
| SubGraph | Generates a subgraph |
