Ecological Inference by Linear Programming under Homogeneity
Integer-adjusting of outputs of the lphom-family functions
Confidence Intervals for lphom estimates
Global error of a lphom estimated table
Implements lclphom algorithm
Implements lp_apriori models
Implements lphom_dual algorithm
Implements the lphom_joint algorithm
Implements lphom algorithm
Implements the nslphom_dual algorithm
Implements the nslphom_joint algorithm
Implements nslphom algorithm
Graphical representation of a RxC ecological inference (vote transfer)...
Print a summary of a lphom-family object
Print a summary of a lphom-family object
Implements rslphom algorithm
Summarize a lphom-family object
Implements the tslphom_dual algorithm
Implements the tslphom_joint algorithm
Implements tslphom algorithm
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, Cultura, Universidades y Empleo, Generalitat Valenciana (grants AICO/2021/257, CIAICO/2023/031) and MICIU/AEI/10.13039/501100011033/FEDER, UE (grant PID2021-128228NB-I00) for supporting this research.