sirir | R Documentation |

This function is achieved by the integration susceptible-infected-recovered (SIR) model with the leave-one-out cross validation technique and ranks network nodes based on their true universal influence. One of the applications of this function is the assessment of performance of a novel algorithm in identification of network influential nodes by considering the SIRIR ranks as the ground truth (gold standard).

```
sirir(
graph,
vertices = V(graph),
beta = 0.5,
gamma = 1,
no.sim = 100,
ncores = "default",
seed = 1234,
loop_verbose = TRUE,
node_verbose = FALSE
)
```

`graph` |
A graph (network) of the igraph class. |

`vertices` |
A vector of desired vertices, which could be obtained by the V function. |

`beta` |
Non-negative scalar. The rate of infection of an individual that is susceptible and has a single infected neighbor. The infection rate of a susceptible individual with n infected neighbors is n times beta. Formally this is the rate parameter of an exponential distribution. |

`gamma` |
Positive scalar. The rate of recovery of an infected individual. Formally, this is the rate parameter of an exponential distribution. |

`no.sim` |
Integer scalar, the number of simulation runs to perform SIR model on the original network as well as perturbed networks generated by leave-one-out technique. You may choose a different no.sim based on the available memory on your system. |

`ncores` |
Integer; the number of cores to be used for parallel processing. If ncores == "default" (default), the number of cores to be used will be the max(number of available cores) - 1. We recommend leaving ncores argument as is (ncores = "default"). |

`seed` |
A single value, interpreted as an integer to be used for random number generation. |

`loop_verbose` |
Logical; whether the accomplishment of the evaluation of network nodes in each loop should be printed (default is TRUE). |

`node_verbose` |
Logical; whether the process of Parallel Socket Cluster creation should be printed (default is FALSE). |

A two-column dataframe; a column containing the difference values of the original and perturbed networks and a column containing node influence rankings

`cent_network.vis`

,
and `sir`

for a complete description on SIR model

Other centrality functions:
`betweenness()`

,
`clusterRank()`

,
`collective.influence()`

,
`degree()`

,
`h_index()`

,
`lh_index()`

,
`neighborhood.connectivity()`

```
## Not run:
set.seed(1234)
My_graph <- igraph::sample_gnp(n=50, p=0.05)
GraphVertices <- V(My_graph)
Influence.Ranks <- sirir(graph = My_graph, vertices = GraphVertices,
beta = 0.5, gamma = 1, ncores = "default", no.sim = 10, seed = 1234)
## End(Not run)
```

influential documentation built on Nov. 19, 2023, 9:06 a.m.

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