Optimum Sample Allocation in Stratified Sampling
Summarizing the Allocation
Integer-valued Optimal Univariate Allocation Under Constraints for Str...
Optimal Univariate Allocation Under Constraints for Stratified Samplin...
Optimum Sample Allocation in Stratified Sampling
Algorithms for Optimum Sample Allocation Under One-Sided Bounds
Minimum Cost Allocation in Stratified Sampling
Random Rounding of Numbers
RNA in version that uses prior information about violations
RNA - Recursive Implementation
Recursive Neyman Algorithm for Optimal Sample Allocation Under Box Con...
Optimal Rounding under Integer Constraints
Integer-valued Optimal Univariate Allocation Under Constraints for Str...
Functions for Optimum Sample Allocation in Stratified Sampling
Variance of the Stratified Estimator
Functions in this package provide solution to classical problem in survey methodology - an optimum sample allocation in stratified sampling. In this context, the optimum allocation is in the classical Tschuprow-Neyman's sense and it satisfies additional lower or upper bounds restrictions imposed on sample sizes in strata. There are few different algorithms available to use, and one them is based on popular sample allocation method that applies Neyman allocation to recursively reduced set of strata. This package also provides the function that computes a solution to the minimum cost allocation problem, which is a minor modification of the classical optimum sample allocation. This problem lies in the determination of a vector of strata sample sizes that minimizes total cost of the survey, under assumed fixed level of the stratified estimator's variance. As in the case of the classical optimum allocation, the problem of minimum cost allocation can be complemented by imposing upper-bounds constraints on sample sizes in strata.