The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
This package provides bootstrap algorithms for Finite Population inference, for estimating the variance of the Horvitz–Thompson estimator.
To install the package from CRAN, run the following code in R:
Or, for the development version:
# if not present, install 'devtools' package
install.packages("devtools")
devtools::install_github("rhobis/bootstrapFP")library(bootstrapFP)
### Generate population data ---
N <- 20; n <- 5
x <- rgamma(N, scale=10, shape=5)
y <- abs( 2*x + 3.7*sqrt(x) * rnorm(N) )
pik <- n * x/sum(x)
### Draw a dummy sample ---
s <- sample(N, n)
### Estimate bootstrap variance ---
bootstrapFP(y = y[s], pik = n/N, B=100, method = "ppSitter")
bootstrapFP(y = y[s], pik = pik[s], B=10, method = "ppHolmberg", design = 'brewer')
bootstrapFP(y = y[s], pik = pik[s], B=10, D=10, method = "ppChauvet")
bootstrapFP(y = y[s], pik = n/N, B=10, method = "dRaoWu")
bootstrapFP(y = y[s], pik = n/N, B=10, method = "dSitter")
bootstrapFP(y = y[s], pik = pik[s], B=10, method = "dAntalTille_UPS", design='brewer')
bootstrapFP(y = y[s], pik = n/N, B=10, method = "wRaoWuYue")
bootstrapFP(y = y[s], pik = n/N, B=10, method = "wChipperfieldPreston")
bootstrapFP(y = y[s], pik = pik[s], B=10, method = "wGeneralised", distribution = 'normal')roberto.sichera@unipa.it.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.