lphom: Ecological Inference by Linear Programming under Homogeneity

Provides a bunch of algorithms based on linear programming for estimating RxC ecological contingency tables (vote transitions matrices) using exclusively aggregate results from voting units under the homogeneity hypothesis. References: Romero, Pavia, Martin and Romero (2020) <doi:10.1080/02664763.2020.1804842>. Pavia and Romero (2021) Improving estimates accuracy of voter transitions. Two new algorithms for ecological inference based on linear programming.

Version: 0.1.4
Depends: R (≥ 3.5.0), lpSolve
Imports: stats
Suggests: ggplot2
Published: 2021-06-09
Author: Jose M. Pavía ORCID iD [aut, cre], Rafael Romero [aut]
Maintainer: Jose M. Pavía <jose.m.pavia at uv.es>
License: GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE]
NeedsCompilation: no
Citation: lphom citation info
CRAN checks: lphom results

Downloads:

Reference manual: lphom.pdf
Package source: lphom_0.1.4.tar.gz
Windows binaries: r-devel: lphom_0.1.4.zip, r-release: lphom_0.1.4.zip, r-oldrel: lphom_0.1.4.zip
macOS binaries: r-release (arm64): lphom_0.1.4.tgz, r-release (x86_64): lphom_0.1.4.tgz, r-oldrel: lphom_0.1.4.tgz
Old sources: lphom archive

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