A function to create cross-validation data.

1 2 | ```
CreateDataCV(net , p = 0.75 , G = 50 ,
net_type = "directed" , deg_thresh = 0 , exclude_end = FALSE)
``` |

`net` |
A three-column matrix whose each row contains information of one edge in the form |

`p` |
Numeric between |

`G` |
Integer. Number of bins. Default value is \code50. |

`net_type` |
String. The type of the network: |

`deg_thresh` |
Integer. We only consider nodes with number of acquired new edges at least this threshold. Default value is |

`exclude_end` |
Logical. If |

.

An object of class `"CV_Data"`

containing the data needed for cross validation.

Thong Pham thongpham@thongpham.net

1. Pham, T., Sheridan, P. & Shimodaira, H. (2016). Nonparametric Estimation of the Preferential Attachment Function in Complex Networks: Evidence of Deviations from Log Linearity, Proceedings of ECCS 2014, 141-153 (Springer International Publishing) (http://dx.doi.org/10.1007/978-3-319-29228-1_13).

2. Pham, T., Sheridan, P. & Shimodaira, H. (2015). PAFit: A Statistical Method for Measuring Preferential Attachment in Temporal Complex Networks. PLoS ONE 10(9): e0137796. doi:10.1371/journal.pone.0137796 (http://dx.doi.org/10.1371/journal.pone.0137796).

3. Pham, T., Sheridan, P. & Shimodaira, H. (2016). Joint Estimation of Preferential Attachment and Node Fitness in Growing Complex Networks. Scientific Reports 6, Article number: 32558. doi:10.1038/srep32558 (www.nature.com/articles/srep32558).

1 2 3 4 | ```
library("PAFit")
net <- GenerateNet(N = 100 , m = 1 , mode = 1 , alpha = 1 , shape = 5 , rate = 5)
data_cv <- CreateDataCV(net$graph)
summary(data_cv)
``` |

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