Package: lphom 0.3.5-5
Jose M. Pavía
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 (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.
Authors:
lphom_0.3.5-5.tar.gz
lphom_0.3.5-5.tar.gz(r-4.5-noble)lphom_0.3.5-5.tar.gz(r-4.4-noble)
lphom_0.3.5-5.tgz(r-4.4-emscripten)lphom_0.3.5-5.tgz(r-4.3-emscripten)
lphom.pdf |lphom.html✨
lphom/json (API)
NEWS
| # Install 'lphom' in R: |
| install.packages('lphom', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- France2017D - 2017 French Presidential Election. Department official results.
- France2017P - 2017 French Presidential Election. Regional provisional results.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:1d5cd108bf. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 30 2024 |
| R-4.5-linux | OK | Oct 30 2024 |
Exports:adjust2integersconfidence_intervals_pjkerror_lphomlclphomlp_apriorilphomlphom_duallphom_jointnslphomnslphom_dualnslphom_jointrslphomtslphomtslphom_dualtslphom_joint
Dependencies:lpSolve
