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snowboot (version 0.5.0)

Oempdegreedistrib: Obtaining an Empirical Network Degree Distribution from Labeled Snowball Sampling with Multiple Inclusion (LSMI).

Description

Oempdegreedistrib is used to obtain the empirical network degree distribution from labeled snowball sampling with multiple inclusion (LSMI).

Usage

Oempdegreedistrib(net, n.seeds, n.neigh, num.sam = 1, seeds = NULL)

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.
n.seeds
A number of seeds in the snowball sample. It must be a positive integer.
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.
num.sam
A number for the LSMI repetitions. Default value is one.
seeds
A matrix of dimension num.sam x n.seeds containing the numeric ids of the seeds to initiate sampling. Each row of the matrix corresponds to one LSMI sample. Note that this is an optional parameter. WARNING: As of now, this

Value

  • A list consisting of
  • samplesA list of length num.sam where each element is a list containing three tables: the frequency of degrees sampled from seeds, non-seeds including duplicated nodes, and non-seeds without duplications. Each sample has its own list.
  • valuesA list of length num.sam where each element is a vector containing the unique degree values sampled in each LSMI.
  • OempA list of length num.sam where each element is a list containing two tables based on different methods to estimating the empirical distribution from the network sample (One list per LSMI).
  • num.samA number for the LSMI repetitions.
  • val.seedsA list of length num.sam where each element is a vector of unique degree values sampled solely from seeds (One vector per LSMI).
  • val.nonseeda list of length num.sam where each element is a vector of unique degree values sampled solely from non-seeds (One vector per LSMI). Note: This item is unreported when n.neigh equals zero.
  • n.seedsthe number of seeds in the snowball sample.
  • n.neighthe number of waves carried out by the snowball sample. See input argument for details.
  • p0.realproportion of nodes from the network with degree zero. Note: p0.real is unreported when n.neigh equals zero.
  • p0.seedsa list of length num.sam where each element is the proportion of seeds with degree zero. (One element per LSMI).
  • ekseeda list of length num.sam where each element is the sample mean of the seeds. Note that This is unreported when n.neigh equals zero.
  • seeds1a matrix of dimension num.sam x n.seeds with the numeric seed ids. Each row corresponds to one LSMI.
  • nodes_of_LSMIa list of length num.sam where each element is vector containing the numeric ids of the nodes sampled using LSMI (One element per LSMI). Note: nodes_of_LSMI is unreported when n.neigh equals zero.

Examples

Run this code
net <- artificial_networks[[1]]
sam.out <- Oempdegreedistrib(net = net, n.seeds = 40, n.neigh = 1, num.sam = 1)

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