regest_strata {sampling}R Documentation

The regression estimator for stratified sampling

Description

Computes the regression estimator of the population total, using the design-based approach, for stratified sampling. The same regression model is used for all strata.

Usage

regest_strata(formula,weights,Tx_strata,strata,pikl,sigma=rep(1,length(weights)),
description=FALSE)

Arguments

formula the regression model formula (y~x).
weights vector of the weights; its length is equal to n, the sample size.
Tx_strata population total of x, the auxiliary variable.
strata vector of stratum identificator.
pikl the joint inclusion probabilities for the sample.
sigma vector of positive values accounting for heteroscedasticity.
description if TRUE, the following components are printed for each stratum: the Horvitz-Thompson estimator, the beta coefficients, their standard error, t_values, p_values, and the covariance matrix. By default, FALSE.

value{The function returns the value of the regression estimator computed as the sum of the stratum estimators.}

Value

The function returns the value of the regression estimator computed as the sum of the stratum estimators.

See Also

regest

Examples

# generates artificial data
y=rgamma(10,3)
x=y+rnorm(10)
Stratum=c(1,1,2,2,2,3,3,3,3,3)
# population size
N=200
# sample size
n=10
# assume proportional allocation, nh/Nh=n/N 
pikl=matrix(0,n,n)
for(i in 1:n)
 {for(j in 1:n)
  if(i!=j)
          pikl[i,j]=pikl[j,i]=n*(n-1)/(N*(N-1))
  pikl[i,i]=n/N
  }
regest_strata(formula=y~x-1,weights=rep(N/n,n),Tx_strata=c(50,30,40),strata=Stratum,pikl,
description=TRUE)

[Package sampling version 2.1 Index]