Package: fastei 0.0.19

Daniel Hermosilla

fastei: Methods for ''A Fast Alternative for the R x C Ecological Inference Case''

Estimates the probability matrix for the R×C Ecological Inference problem using the Expectation-Maximization Algorithm with four approximation methods for the E-Step, and an exact method as well. It also provides a bootstrap function to estimate the standard deviation of the estimated probabilities. In addition, it has functions that aggregate rows optimally to have more reliable estimates in cases of having few data points. For comparing the probability estimates of two groups, a Wald test routine is implemented. The library has data from the first round of the Chilean Presidential Election 2021 and can also generate synthetic election data. Methods described in Thraves, Charles; Ubilla, Pablo; Hermosilla, Daniel (2024) ''A Fast Ecological Inference Algorithm for the R×C case'' <doi:10.2139/ssrn.4832834>.

Authors:Charles Thraves [aut], Pablo Ubilla [aut], Daniel Hermosilla [aut, cre]

fastei_0.0.19.tar.gz
fastei_0.0.19.tar.gz(r-4.7-arm64)fastei_0.0.19.tar.gz(r-4.7-x86_64)fastei_0.0.19.tar.gz(r-4.6-arm64)fastei_0.0.19.tar.gz(r-4.6-x86_64)
fastei_0.0.19.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
fastei/json (API)

# Install 'fastei' in R:
install.packages('fastei', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/danielhermosilla/ecological-inference-elections/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

3.62 score 1 stars 14 scripts 488 downloads 9 exports 2 dependencies

Last updated from:260ad6c135. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK148
linux-devel-x86_64OK169
source / vignettesOK260
linux-release-arm64OK150
linux-release-x86_64OK150
wasm-releaseOK132

Exports:bootstrapeimget_agg_optget_agg_proxyget_eim_chilerun_emsave_eimsimulate_electionwaldtest

Dependencies:jsonliteRcpp

Demonstration of the package usage

Rendered fromdemonstration.Rmdusingknitr::rmarkdownon Jun 19 2026.

Last update: 2026-05-08
Started: 2025-05-16