calibration: Calibration
In tereom/quickcountmx: Estimate Election Results Mexico

Description Usage Arguments Details Value See Also

The functions calibration_party and calibration_prop perform simulation from past election results, fit a model calling (mrp_party_estimation or mrp_estimation) for each simulation and return posterior simulations along actual outcomes, these can later be used to compute calibration summaries with the corresponding function: summary_calibration_party or summary_calibration. calibration_party is useful to calibrate individual models of total votes for a given party and calibration_prop is useful to analyse estimates for proportion of votes per party.

calibration_party(data, party, stratum, frac = 1, n_iter = 2000,
  n_burnin = 500, n_chains = 3, seed = NA, cl_cores = 14, n_rep = 5,
  model_string = NULL)

calibration_prop(data, ..., stratum, frac = 1, n_iter = 2000,
  n_burnin = 500, n_chains = 3, seed = NA, cl_cores = 3, n_rep = 5,
  model_string = NULL, num_missing_strata = 0)

summary_calibration_party(calib_run_party, alpha_r = 0.05)

summary_calibration(calib_run, alpha_r = 0.05)

`data`	A `data.frame` with variables: ln_total, region, distrito_loc_17, tamano_md, tamano_gd, casilla_ex and the column with number of votes for the party.
`party`	Unquoted variable indicating the column from the data.frame to be modeled.
`stratum`	If sampling the data, unquoted variable indicating the column from the data.frame to be used as strata. The strata will also be used in the hierarchical structure of the model.
`frac`	If sampling the data, numeric value indicating the fraction of the data to sample, the sample is selected using stratified sampling with probability proportional to size.
`n_iter`	Number of iterations, burnin size and chains. to be used in `jags`.
`n_burnin`	Number of iterations, burnin size and chains. to be used in `jags`.
`n_chains`	Number of iterations, burnin size and chains. to be used in `jags`.
`seed`	An integer vector of length 7 to be send to `clusterSetRNGStream`.
`cl_cores`	Number of cores, parameter is used in `makeCluster`.
`n_rep`	Number of repetitions of sample selection and model fitting.
`model_string`	String indicating the model to fit.
`alpha_r`	Calibration examines coverage of (1-alpha_r)*100 intervals.

The functions are computationally demanding, they were designed to run on computers with more than 16 cores.

data.frame with posterior simulation of total votes (if using calibration_party) or proportions (if using calibration_prop) for each repetiton of sample selection and model fitting.

mrp_estimation, mrp_party_estimation

tereom/quickcountmx documentation built on Dec. 2, 2019, 9:58 p.m.