Description Usage Arguments Value Examples

This is the parallelised version of the skeleton function in the pcalg package.

1 2 3 4 |

`suffStat` |
Sufficient statistics: List containing all necessary elements for the conditional independence decisions in the function indepTest. |

`indepTest` |
Predefined function for testing conditional independence. The function is internally called as indepTest(x,y,S,suffStat) and tests conditional independence of x and y given S. Here, x and y are variables, and S is a (possibly empty) vector of variables (all variables are denoted by their column numbers in the adjacency matrix). suffStat is a list containing all relevant elements for the conditional independence decisions. The return value of indepTest is the p-value of the test for conditional independence. |

`alpha` |
significance level (number in (0; 1) for the individual conditional independence tests. |

`labels` |
(optional) character vector of variable (or "node") names. Typically preferred to specifying p. |

`p` |
(optional) number of variables (or nodes). May be specified if labels are not, in which case labels is set to 1:p. |

`method` |
Character string specifying method; the default, "parallel" provides an efficient skeleton, see skeleton_parallel. |

`mem.efficient` |
Uses less amount of memory at any time point while running the algorithm |

`workers` |
Creates a set of copies of R running in parallel and communicating over sockets. |

`num_workers` |
The numbers of cores CPU as numbers of workers to run the algorithm |

`m.max` |
Maximal size of the conditioning sets that are considered in the conditional independence tests. |

`fixedGaps` |
A logical matrix of dimension p*p. If entry [i,j] or [j,i] (or both) are TRUE, the edge i-j is removed before starting the algorithm. Therefore, this edge is guaranteed to be absent in the resulting graph. |

`fixedEdges` |
A logical matrix of dimension p*p. If entry [i,j] or [j,i] (or both) are TRUE, the edge i-j is never considered for removal. Therefore, this edge is guaranteed to be present in the resulting graph. |

`NAdelete` |
logical needed for the case indepTest(*) returns NA. If it is true, the corresponding edge is deleted, otherwise not. |

`verbose` |
if TRUE, detailed output is provided. |

An object of class "pcAlgo" (see pcAlgo in the pcalg package) containing an estimate of the skeleton of the underlying DAG, the conditioning sets (sepset) that led to edge removals and several other parameters.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
##########################################
## Using skeleton_parallel without mem.efficeient
##########################################
library(pcalg)
library(parallel)
data("gmG")
p<-ncol(gmG$x)
suffStat<-list(C=cor(gmG$x),n=nrow(gmG$x))
skeleton_parallel(suffStat,indepTest=gaussCItest,p=p,method="parallel",alpha=0.01,num_workers=2)
##########################################
## Using skeleton_parallel with mem.efficeient
##########################################
library(pcalg)
library(parallel)
data("gmG")
p<-ncol(gmG$x)
suffStat<-list(C=cor(gmG$x),n=nrow(gmG$x))
skeleton_parallel(suffStat,indepTest=gaussCItest,p=p,method="parallel",
alpha=0.01,num_workers=2,mem.efficient=TRUE)
``` |

```
n=5000,p=8
Num CI Tests= 49 136 54 0 ,Total CI Tests= 239 ,Total Time= 0.027
Object of class 'pcAlgo', from Call:
skeleton_parallel(suffStat = suffStat, indepTest = gaussCItest,
alpha = 0.01, p = p, method = "parallel", num_workers = 2)
Number of undirected edges: 8
Number of directed edges: 0
Total number of edges: 8
sh: 1: egrep: Permission denied
n=5000,p=8
Num CI Tests= 49 136 54 0 ,Total CI Tests= 239 ,Total Time= 0.024
Object of class 'pcAlgo', from Call:
skeleton_parallel(suffStat = suffStat, indepTest = gaussCItest,
alpha = 0.01, p = p, method = "parallel", mem.efficient = TRUE,
num_workers = 2)
Number of undirected edges: 8
Number of directed edges: 0
Total number of edges: 8
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.