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 exclusively aggregate data (from voting units). References: Romero, Pavía, Martín and Romero (2020) <doi:10.1080/02664763.2020.1804842>. Pavía and Romero (2021a) <doi:10.31124/advance.14716638.v1>. Pavía and Romero (2021b) Symmetry estimating R×C vote transfer matrices from aggregate data.

Version: 0.3.1-1
Depends: R (≥ 3.5.0)
Imports: stats, lpSolve
Suggests: ggplot2, scales, Rsymphony (≥ 0.1-30)
Published: 2022-03-21
Author: Jose M. Pavía ORCID iD [aut, cre], Rafael Romero [aut]
Maintainer: Jose M. Pavía <jose.m.pavia at uv.es>
License: EPL | file LICENSE
NeedsCompilation: no
Citation: lphom citation info
CRAN checks: lphom results


Reference manual: lphom.pdf


Package source: lphom_0.3.1-1.tar.gz
Windows binaries: r-devel: lphom_0.3.1-1.zip, r-release: lphom_0.3.1-1.zip, r-oldrel: lphom_0.3.1-1.zip
macOS binaries: r-release (arm64): lphom_0.3.1-1.tgz, r-oldrel (arm64): lphom_0.3.1-1.tgz, r-release (x86_64): lphom_0.3.1-1.tgz, r-oldrel (x86_64): lphom_0.3.1-1.tgz
Old sources: lphom archive


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