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,
MOSAlloc 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. Conic quadratic problem representations are parsed to the Embedded Conic Solver from the ECOSolveR package. See Willems (2025, doi:10.25353/ubtr-9200-484c-5c89) for a detailed description of the theory behind MOSAlloc.
Install the latest CRAN version of MOSAlloc by entering the following in R:
install.packages("MOSAlloc")
You can install MOSAlloc (development version) from GitLab using the remotes package:
# install.packages("remotes")
remotes::install_gitlab("willemsf/mosalloc")
Cite package as:
Willems, F. (2025). A Framework for Multiobjective and Uncertain Resource Allocation Problems in Survey Sampling based on Conic Optimization. Ph.D. thesis, Trier University, Trier, Germany. https://doi.org/10.25353/ubtr-9200-484c-5c89.
This package is licensed under the GNU General Public License, version 3 or later (GPL-3.0-or-later).
Felix Willems, Trier University, Email: [email protected]
Maintainer: Felix Willems [email protected]
Supervised by Prof. Dr. Ralf Münnich, Trier University.
Neyman, J. (1934). On the Two Different Aspects of the Representative Method: The Method of Stratified Sampling and the Method of Purposive Selection. Journal of the Royal Statistical Society, 97(4), 558–625.
Tschuprow, A.A. (1923). On the Mathematical Expectation of the Moments of Frequency Distribution in the Case of Correlated Observations. Metron, 2(3,4), 461-493, 646-683.
Willems, F. (2025). A Framework for Multiobjective and Uncertain Resource Allocation Problems in Survey Sampling based on Conic Optimization (Doctoral dissertation). Trier University. https://doi.org/10.25353/ubtr-9200-484c-5c89.