varEst: Estimator of the approximated variance for balanced sampling

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/varStrat.R

Description

Estimator of the approximated variance for balanced sampling

Usage

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varEst(X, strata, pik, s, y)

Arguments

X

A matrix of size (N x p) of auxiliary variables on which the sample must be balanced.

strata

A vector of integers that represents the categories.

pik

A vector of inclusion probabilities.

s

A sample (vector of 0 and 1, if rejected or selected).

y

A variable of interest.

Details

This function gives an estimator of the approximated variance of the Horvitz-Thompson total estimator presented by Hasler C. and Tillé Y. (2014).

Value

a scalar, the value of the estimated variance.

Author(s)

Raphaël Jauslin raphael.jauslin@unine.ch

References

Hasler, C. and Tillé, Y. (2014). Fast balanced sampling for highly stratified population. Computational Statistics and Data Analysis, 74:81-94.

See Also

varApp

Examples

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N <- 1000
n <- 400
x1 <- rgamma(N,4,25)
x2 <- rgamma(N,4,25)

strata <- as.matrix(rep(1:40,each = 25)) # 25 strata
Xcat <- disjMatrix(strata)
pik <- rep(n/N,N)
X <- as.matrix(matrix(c(x1,x2),ncol = 2))
 
s <- stratifiedcube(X,strata,pik)
 
y <- 20*strata + rnorm(1000,120) # variable of interest
# y_ht <- sum(y[which(s==1)]/pik[which(s == 1)]) # Horvitz-Thompson estimator
# (sum(y_ht) - sum(y))^2 # true variance
varEst(X,strata,pik,s,y)
varApp(X,strata,pik,y)

StratifiedSampling documentation built on Sept. 24, 2021, 5:07 p.m.