Description Usage Arguments Value Author(s) References Examples

View source: R/NetworkToolbox--master.R

Bootstraps the sample with replace to compute walktrap reliability (still in testing phase)

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`data` |
A set of data |

`normal` |
Should data be transform to a normal distribution? Defaults to FALSE. Data is not transformed to be normal. Set to TRUE if data should be transformed to be normal |

`n` |
Number of people to use in the bootstrap. Defaults to full sample size |

`iter` |
Number of bootstrap iterations. Defaults to 100 iterations |

`filter` |
Set filter method. Defaults to "TMFG" |

`method` |
Defaults to "louvain". Set to "walktrap" for the walktrap algorithm |

`na.data` |
How should missing data be handled?
For "pairwise" deletion |

`steps` |
Number of steps to use in the walktrap algorithm. Defaults to 4. Use a larger number of steps for smaller networks |

`...` |
Additional arguments for network filtering methods |

The factors and their proportion found across bootstrapped samples (i.e., their likelihood)

Alexander Christensen <[email protected]>

Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008).
Fast unfolding of communities in large networks.
*Journal of Statistical Mechanics: Theory and Experiment*, *2008*(10), P10008.

Csardi, G., & Nepusz, T. (2006).
The igraph software package for complex network research.
*InterJournal, Complex Systems*, *1695*(5), 1-9.

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AlexChristensen/NetworkToolbox documentation built on Feb. 15, 2018, 10:12 p.m.

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