Constraint Multiobjective Sample Allocation
Description
Provides a framework for multipurpose optimal resource allocation in survey sampling,
extending the classical optimal allocation principles introduced by Tschuprow (1923) and
Neyman (1934) to multidomain and multivariate allocation problems. The primary method
mosalloc() allows for the consideration of precision and cost constraints at the subpopulation
level while minimizing either a vector of sampling errors or survey costs across a broad range
of optimal sample allocation problems. The approach supports both single- and multistage
designs. For single-stage stratified random sampling, the mosallocSTRS() function offers a user-
friendly interface. Sensitivity analysis is supported through the problem's dual variables, which
are naturally obtained via the internal use of the Embedded Conic Solver from the 'ECOSolveR'
package. See Willems (2025, ) for a detailed description
of the theory behind 'MOSAlloc'.