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 (2024) <doi:10.1177/00491241221092725>. Pavía and Romero (2024) <doi:10.1093/jrsssa/qnae013>. Pavía (2023) <doi:10.1007/s43545-023-00658-y>. Pavía (2024) <doi:10.1080/0022250X.2024.2423943>. Pavía (2024) <doi:10.1177/07591063241277064>. 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 (grants AICO/2021/257, CIAICO/2023/031) and Ministerio de Economía e Innovación (grant PID2021-128228NB-I00) for supporting this research.

Getting started

Package details

AuthorJose M. Pavía [aut, cre] (<https://orcid.org/0000-0002-0129-726X>), Rafael Romero [aut]
MaintainerJose M. Pavía <jose.m.pavia@uv.es>
LicenseEPL | file LICENSE
Version0.3.5-6
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("lphom")

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lphom documentation built on April 12, 2025, 1:20 a.m.