README.md

In bootstrapFP: Bootstrap Algorithms for Finite Population Inference

bootstrapFP

Description

This package provides bootstrap algorithms for Finite Population inference, for estimating the variance of the Horvitz–Thompson estimator.

Installation

To install the package from CRAN, run the following code in R:

install.packages("bootstrapFP")

Or, for the development version:

# if not present, install 'devtools' package
install.packages("devtools")
devtools::install_github("rhobis/bootstrapFP")

Usage

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')

More

• Please, report any bug or issue here.
• For more information, please contact the maintainer at [e-mail].

bootstrapFP documentation built on Sept. 3, 2023, 1:08 a.m.