Constraint Multiobjective Sample Allocation.

MOSAlloc

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.

Installation

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")

Citation

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.

Licensing

This package is licensed under the GNU General Public License, version 3 or later (GPL-3.0-or-later).

Author / Maintainer

Felix Willems, Trier University, Email: [email protected]

Maintainer: Felix Willems [email protected]

Supervised by Prof. Dr. Ralf Münnich, Trier University.

References

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.