BSSM_FD: Optimal Allocation - Minimum Coefficient of Variation

In stratbr: Optimal Stratification in Stratified Sampling

Description

Function that uses an integer programming formulation for allocation of the overall sample size n to the strata, for the following purpose: Coefficient of Variation of the estimate of total for the survey variable is minimized.

Usage

BSSM_FD(Nh, Sh2x, n, H, nmin = 2, X, takeall = FALSE)

Arguments

Nh	Vector with number of population elements, or population size, in stratum h
Sh2x	Vector with population variance of the variable X in stratum h.
n	Sample size.
H	Number of strata.
nmin	Minimum sample size (smallest possible sample size in any stratum). The default is 2.
X	Population Total
takeall	Take-all stratum (takeall=TRUE) => nH=NH.

Value

solution

Vector with sample of size by stratum and coefficient of variation for the estimator of total of the stratification variable considered.

Author(s)

Jose Brito ([e-mail]), Pedro Silva, Gustavo Semaan and Nelson Maculan.

References

Brito, J.A.M, Silva, P.L.N.,Semaan, G.S. and Maculan, N. (2015). Integer Programming Formulations Applied to Optimal Allocation in Stratified Sampling. Survey Methodology, 41: 427-442.

Examples

X<-round(100*runif(50))
Nh<-c(10,20,20)
Sh2x<-c(var(X[1:10]),var(X[11:30]),var(X[31:50]))
aloc1<-BSSM_FD(Nh,Sh2x,n=40,H=3,nmin=2,sum(X),takeall=TRUE)
Nh<-c(49,78,20,39,73,82,89)
X<-542350
Sh2x<-c(4436978,5581445,33454902,5763294,8689167,3716130,13938505)
aloc2<-BSSM_FD(Nh,Sh2x,n=100,H=7,nmin=2,X)

stratbr documentation built on May 1, 2019, 9:24 p.m.