NOTE: JAGS is required to use the current version of this package
# Install the development version (requires the package "devtools", so install it first if it is not installed already)
devtools::install_github("DiogoFerrari/eforensics")
# If you don't want to update the dependencies, use: (you may need to install some dependencies manually)
devtools::install_github("DiogoFerrari/eforensics", dependencies=F)
In R, check help(eforensics)
library(eforensics)
ef_models()
model = 'bl'
## simulating data and parameters
## ------------------------------
help(ef_simulateData)
sim_data = ef_simulateData(n=1000, nCov=1, nCov.fraud=2, model=model)
data = sim_data$data %>% tibble::as_data_frame()
## mcmc parameters
## ---------------
mcmc = list(burn.in=1, n.adapt=10, n.iter=200, n.chains=2)
## samples
## -------
help(eforensics)
samples = eforensics(
w ~ x1.w ,
a ~ x1.a,
mu.iota.s ~ x1.iota.s + x2.iota.s,
mu.chi.m ~ x1.chi.m + x2.chi.m ,
mu.chi.s ~ x1.chi.s + x2.chi.s ,
mu.iota.m ~ x1.iota.m + x2.iota.m ,
data=data,
elegible.voters="N",
model=model, mcmc=mcmc, get.dic=0,
parameters = "all")
## summary
## -------
summary(samples)
summary(samples, join.chains=T)
## compare with the true
## ---------------------
True = ef_get_true(sim_data)
summary(samples, join.chains=T) %>% dplyr::left_join(., True , by="Parameter")
## plots
## -----
ef_plot(samples)
ef_plot(samples, True)
ef_plot(samples, True, parse=T)
ef_plot(samples, plots = c("Abstention and Vote", "Fraud Probability" ))
ef_plot(samples, plots = c( "Fraud Probability" ))