sample_about_one_seed: Snowball sampling with multiple inclusion around a single seed
Description
This function performs snowball sampling with multiple inclusions (LSMI) around a
single seed.
Usage
sample_about_one_seed(net, seed0, n.neigh = 1)
Arguments
net
A network object that is list containing:
[object Object],[object Object],[object Object]
The object can be created by local.network.MR.new5 or
it can be imported.
seed0
num. Id of a seed to be sampled around.
n.neigh
A number of waves to be sampled around each seed in LSMI.
For example, n.neigh = 0 corresponds to seeds only, and n.neigh = 1
corresponds to sampling seeds and their first neighbors).
Note that the algorithm allows for multiple inclusions.
Value
a list containing:
seedseed0 num. Id of a seed to be sampled around.
sampleNA vector of numeric ids of the nodes from
LSMI along with the original seed. This vector may have
duplicates, since the algorithm allows for multiple inclusions.
unodeA vector containing the unique values in $sampleN.
nodes.wavesA list of length n.neigh containing vectors where
each vector reports numeric ids of nodes sampled in a particular wave.
References
Thompson, M. E., Ramirez Ramirez, L. L., Lyubchich, V. and
Gel, Y. R. (2015), Using the bootstrap for statistical inference
on random graphs. Can J Statistics. doi: 10.1002/cjs.11271