vEst: Variance Estimation for balanced sample

In StratifiedSampling: Different Methods for Stratified Sampling

Variance Estimation for balanced sample

Description

Estimated variance approximation calculated as the conditional variance with respect to the balancing equations of a particular Poisson design. See Tillé (2020)

Usage

vEst(Xauxs, piks, ys)

Arguments

Xauxs	A matrix of size (n x p) of auxiliary variables on which the sample must be balanced.
piks	A vector of inclusion probabilities. The vector has the size of the sample s.
ys	A variable of interest.The vector has the size n of the sample s.

Value

Estimated variance of the horvitz-thompson estimator.

Author(s)

Raphaël Jauslin [e-mail]

References

Tillé, Y. (2020), Sampling and Estimation from finite populations, Wiley,

See Also

vDBS vApp

Examples

N <- 100 
n <- 40
x1 <- rgamma(N,4,25)
x2 <- rgamma(N,4,25)

pik <- rep(n/N,N)
Xaux <- cbind(pik,as.matrix(matrix(c(x1,x2),ncol = 2)))
Xspread <- cbind(runif(N),runif(N))
  

s <- balseq(pik,Xaux,Xspread)
  
y <- Xaux%*%c(1,1,3) + rnorm(N,120) # variable of interest
  
vEst(Xaux[s,],pik[s],y[s])
vDBS(Xaux[s,],Xspread[s,],pik[s],y[s])
vApp(Xaux,pik,y)

StratifiedSampling documentation built on Oct. 26, 2022, 5:09 p.m.