eiCircles: Ecological Inference of RxC Tables by Overdispersed-Multinomial Models

Estimates RxC (R by C) vote transfer matrices (ecological contingency tables) from aggregate data using the model described in Forcina et al. (2012), as extension of the model proposed in Brown and Payne (1986). Allows incorporation of covariates. References: Brown, P. and Payne, C. (1986). ”Aggregate data, ecological regression and voting transitions”. Journal of the American Statistical Association, 81, 453–460. <doi:10.1080/01621459.1986.10478290>. Forcina, A., Gnaldi, M. and Bracalente, B. (2012). ”A revised Brown and Payne model of voting behaviour applied to the 2009 elections in Italy”. Statistical Methods & Applications, 21, 109–119. <doi:10.1007/s10260-011-0184-x>. Pavia, J.M, and Forcina, A. (2026). ”Simulating electoral behavior”. Modeling Decisions for Artificial Intelligence, MDAI 2025. Lecture Notes in Computer Science, vol 15957, Torra, V., Narukawa, Y., Domingo-Ferrer, J. (eds), Springer, Cham, pp. 54-65. <doi:10.1007/978-3-032-00891-6_5>. Acknowledgements: The authors wish to thank Consellería de Educación, Cultura, Universidades y Empleo, Generalitat Valenciana (grant CIAICO/2023/031) and MICIU/AEI/10.13039/501100011033/FEDER, EU (grant PID2021-128228NB-I00) for supporting this research.

Version:	0.0.1-14
Imports:	stats, NlcOptim (≥ 0.6)
Suggests:	ggplot2, scales
Published:	2026-03-17
DOI:	10.32614/CRAN.package.eiCircles
Author:	Antonio Forcina [aut], Jose M. Pavía [aut, cre]
Maintainer:	Jose M. Pavía <jose.m.pavia at uv.es>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	eiCircles results

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