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.
You can install the development version of MOSAlloc 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: willemsf@uni-trier.de
Maintainer: Felix Willems mail.willemsf+MOSAlloc@gmail.com
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.