Description Usage Arguments Details Value References See Also Examples

Obtain one big LSMI – with `max(n.seeds)`

seeds and `n.wave`

waves around each – and subsample seeds to create smaller LSMIs (with less
seeds and/or waves). The function is primarily used in cross-validation.

1 | ```
lsmi_union(net, n.seeds, n.wave, seeds = NULL)
``` |

`net` |
a network object that is a list containing: `degree` the degree sequence of the network, which is an `integer` vector of length*n*;`edges` the edgelist, which is a two-column matrix, where each row is an edge of the network; `n` the network order (i.e., number of nodes in the network).
The network object can be simulated by |

`n.seeds` |
an integer vector of numbers of seeds for snowball sampling
(cf. a single integer |

`n.wave` |
an integer defining the number of waves (order of the neighborhood)
to be recorded around the seed in the LSMI. For example, |

`seeds` |
a vector of numeric IDs of pre-specified seeds. If specified, LSMIs are constructed around each such seed. |

Note that the produced LSMIs are slightly different from those described by \insertCitegel_etal_2017;textualsnowboot. The current R implementation produces smaller LSMIs by subsetting the seeds, not by new sampling of seeds from the network and growing completely new LSMIs, as it was done by \insertCitegel_etal_2017;textualsnowboot. See the details in Figure 3 by \insertCitechen_etal_2018_snowboot;textualsnowboot

A list with two elements:

`lsmi_big` |
LSMI with |

`sequence_seeds` |
A list of length equal to |

`sample_about_one_seed`

, `lsmi`

, `lsmi_cv`

1 2 | ```
net <- artificial_networks[[1]]
a <- lsmi_union(net, n.seeds = c(5, 10, 15), n.wave = 2)
``` |

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