Description Usage Arguments Value Author(s) References Examples

View source: R/NetworkToolbox--master.R

Bootstraps the sample with replace to compute walktrap reliability

1 2 3 4 5 |

`data` |
A set of data |

`normal` |
Should data be transformed 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".
See EBICglasso and |

`weighted` |
Should network be weighted? Defaults to TRUE. Set to FALSE to produce an unweighted (binary) network |

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

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

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

`cores` |
Number of computer processing cores to use for bootstrapping samples.
Defaults to |

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

Returns the number of factors and their relative frequency found across bootstrapped samples

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.

1 2 3 4 5 6 |

AlexChristensen/NetworkToolbox documentation built on May 6, 2018, 7:39 p.m.

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.