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:
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)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.