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lphom

Ecological Inference by Linear Programming under Homogeneity

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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.

Citation lphom citation info

Key Metrics

Version 0.3.5-5
R ≥ 3.5.0
Published 2024-03-03 61 days ago
Needs compilation? no
License EPL
License File
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Maintainer

Maintainer

Jose M. Pavía

jose.m.pavia@uv.es

Authors

Jose M. Pavía

aut / cre

Rafael Romero

aut

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

lphom archive

Depends

R ≥ 3.5.0

Imports

stats
lpSolve ≥ 5.6.18

Suggests

ggplot2
scales
Rsymphony ≥ 0.1-30