rdssampleC: Create RDS samples with given characteristics

Description

Create RDS samples with given characteristics

Usage

rdssampleC(
  net,
  nnodes = network.size(net),
  nsamp0,
  fixinitial,
  nsamp,
  replace,
  coupons,
  select = NULL,
  bias = NULL,
  rds.samp = NULL,
  seed.distribution = NULL,
  attrall = FALSE,
  trait.variable = "disease",
  nsims = 1,
  seeds = NULL,
  prob.network.recall = 1,
  verbose = TRUE
)

Value

A list with the following elements: nsample: vector of indices of sampled nodes wsample: vector of waves of each sampled node degsample: vector of degrees of sampled nodes attrsample: vector of attrs of sampled nodes toattr: vector of numbers of referrals to attrsd nodes tonoattr: vector of number of referrans to unattrsd nominators: recruiter of each sample

Arguments

net: the network object from which to draw a sample
nnodes: the number of nodes in the network [at least as default]
nsamp0: the number of seeds to be drawn (i.e. the size of the 0th wave of sampling)
fixinitial: a variable that indicates the distribution from which to draw the initial seeds, if the seeds variable is NULL and the seed.distribution variable is NULL
nsamp: number of individuals in each RDS sample
replace: sampling with replacement
coupons: number of coupons
select: not used
bias: not used
rds.samp: not used
seed.distribution: a variable [what kind?] that indicates the distribution from which to draw the initial seeds
attrall: Whether all the information about the sample should be returned [??]
trait.variable: attribute of interest
nsims: number of RDS samples to draw
seeds: an array of seeds. Default is NULL, in which case the function draws the seeds from the nodes of the network.
prob.network.recall: simulates the probability that an individual will remember any particular link
verbose: Print verbose output