X_matrix <- X_matrix_fun_aug(proposal, cov)
#approximate the poisson model with a glm
mu <- 0.01
#Setup
- App_True_Graph.rds is the true subgraph between study participants used in RDS_App_Sim_No_Aux.R and RDS_App_Sim_Aux.R.
# Simulations
- run_rds_gen.sh generates graphs of different sizes and densities (the settings that are listed in Tables 1,3,4 and 5) using Generate_RDS_Study.R. We toggle between the graph settings for Simulations 1 and 2 of Section 5 by setting the stochastic_block argument equal to TRUE or FALSE respectively (for the simulations in Section 3 set stochastic_block equal to FALSE). Generate_RDS_Study.R then simulates an RDS of size n=100 on the generated graph and saves the output.
#### Setup
- Download the data from Wu et al. (2017) (link to data set: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5667832/bin/pone.0185711.s004.csv) and save it as PWID_Estonia_RDS.xls. This is the data referenced in Section 6 that records the RDS on People Who Inject Drugs (PWID) conducted in the Kohtla-Jarve region in Estonia.
