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lphom: Ecological Inference by Linear Programming under Homogeneity
Provides a bunch of algorithms based on linear programming for estimating, under
the homogeneity hypothesis, RxC ecological contingency tables (or vote transition matrices)
using mainly aggregate data (from voting units).
References:
Pavía and Romero (2022) <doi:10.1177/00491241221092725>.
Pavía (2023) <doi:10.1007/s43545-023-00658-y>.
Pavía and Romero (2024) <doi:10.1093/jrsssa/qnae013>.
Pavía (2024) A local convergent ecological inference algorithm for RxC tables.
Pavía and Penadés (2024). A bottom-up approach for ecological inference.
Romero, Pavía, Martín and Romero (2020) <doi:10.1080/02664763.2020.1804842>.
Acknowledgements:
The authors wish to thank Consellería de Educación, Universidades y Empleo, Generalitat Valenciana (grant AICO/2021/257) and Ministerio de Economía e Innovación (grant PID2021-128228NB-I00) for supporting this research.
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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[aut, cre],
Rafael Romero [aut]