neighb {Neighboot} | R Documentation |
This function estimate standard errors and compute confidence intervals from an RDS sample using the neighborhood bootstrap method.
neighb(RDS.data, quant=c(0.025, 0.975),
method=c("percentile","Wald"), B=1000)
RDS.data |
A list containing the following objects:
|
quant |
a vector of positive integers between 0 and 1, representing quantiles to be estimated. |
method |
a character string representing the method for computing confidence intervals,
either |
B |
the number of bootstrap repetitions. Default is 1000. |
The function neighb
compute standard errors and confidence intervals using
the neighborhood bootstrap method for RDS. Confidence intervals can be computed using
the percentile method or the studentized method.
A matrix of estimated standard errors and quantiles. Each row represents a trait.
Mamadou Yauck <yauck.mamadou@uqam.ca> and Erica E. M. Moodie.
#Load the synthetic population network dataset.
data("pop.network")
#Draw an RDS sample from the simulated network using the sampleRDS function
#from the package RDStreeboot.
require(RDStreeboot)
RDS.samp <- sample.RDS(pop.network$traits, pop.network$adj.mat, 200, 10,
3, c(1/6,1/3,1/3,1/6), FALSE)
#Compute 95\% confidence intervals using the percentile method
neighb(RDS.data=RDS.samp, quant=c(0.025, 0.975),method="percentile", B=100)