Package: spikes 1.1

Arturas Rozenas

spikes: Detecting Election Fraud from Irregularities in Vote-Share Distributions

Applies re-sampled kernel density method to detect vote fraud. It estimates the proportion of coarse vote-shares in the observed data relative to the null hypothesis of no fraud.

Authors:Arturas Rozenas

spikes_1.1.tar.gz
spikes_1.1.tar.gz(r-4.7-any)spikes_1.1.tar.gz(r-4.6-any)
spikes_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
spikes/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 8 scripts 257 downloads 18 exports 11 dependencies

Last updated from:eadb7e35fc. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK126
source / vignettesOK138
linux-release-x86_64OK132
wasm-releaseOK89

Exports:abupdateconfIntdmbetadmbetabinomem.updateest.densityfraudinitplot.outrange01resamplermnormroundrsamp.matspikessummary.outy.v

Dependencies:bbmlebdsmatrixcodaemdbooklatticeMASSMatrixmvtnormnumDerivplyrRcpp

Readme and manuals

Help Manual

Help pageTopics
Credible intervalconfInt
Example datadata
Ouput objectoutput
Plots output of 'spikes'plot.out
Fraud-detection from vote-share dataspikes
Internal functionsa bupdate dmbeta dmbetabinom em.update est.density fraud init range01 resample rmnorm roundr samp.mat y.v
Summarizesummary.out