• Corpus ID: 49244017

Optimal sample allocation for the Incomplete Stratified Sampling design

@inproceedings{Vitiis2015OptimalSA,
  title={Optimal sample allocation for the Incomplete Stratified Sampling design},
  author={Claudia De Vitiis and Paolo Righi and Marco Dionisio Terribili},
  year={2015}
}
For sampling surveys aiming at producing estimates for different domains of interest, a sampling design widely adopted in official statistics is the Stratified Simple Random Sampling (SSRS) design in which strata are defined by crossing of the variables that define the domains of estimate. When there are many strata, the SSRS design could be inefficient. We propose an alternative sampling design denoted as Incomplete Stratified Sampling (ISS) design. The design exploits all the potential… 

Figures and Tables from this paper

References

SHOWING 1-10 OF 13 REFERENCES
On sample allocation for efficient domain estimation
Sample allocation issues are studied in the context of estimating sub-population (stratum or domain) means as well as the aggregate population mean under stratified simple random sampling. A
Optimal Allocation in the Multi-way Stratification Design for Business Surveys
Commonly, the business surveys produce estimates for a huge number of domains that define two or more partitions of the target population. When domain indicator variables are known at population
An optimal multivariate stratified sampling design using auxiliary information: an integer solution using goal programming approach
In multivariate stratified random sampling, for practical purposes we need an allocation which is optimum in some sense for all characteristics because the individual optimum allocations usually
On Sample Allocation in Multivariate Surveys
The problem of a sample allocation between strata in the case of multiparameter surveys is considered in this article. There are several multivariate sample allocation methods and, moreover, several
Determining the optimum strata boundary points using dynamic programming
Optimum stratification is the method of choosing the best boundaries that make strata internally homogeneous, given some sample allocation. In order to make the strata internally homogenous, the
Using Composite Estimators to Improve Both Domain and Total Area Estimation
In this article we propose using small area estimators to improve the estimates of both the small and large area parameters. When the objective is to estimate parameters at both levels accurately,
Efficient balanced sampling: The cube method
A balanced sampling design is defined by the property that the Horvitz--Thompson estimators of the population totals of a set of auxiliary variables equal the known totals of these variables.
Power Allocations: Determining Sample Sizes for Subnational Areas
TLDR
A simple allocation method is suggested for achieving reliable national and subnational estimates of population size and importance in subnational areas.
Principi e metodi del software generalizzato per la definizione
  • 1998
...
1
2
...