mrp_estimation: Compute all postratified estimates
In tereom/quickcountmx: Estimate Election Results Mexico

Description Usage Arguments Value See Also Examples

This function calls mrp_party_estimation using all the parties specified in '...', once there is an estimation of the number of votes for each party/candidate it computes the proportion of votes for each one.

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mrp_estimation(data, ..., stratum, frac = 1, n_iter = 2000,
  n_burnin = 500, n_chains = 3, seed = NA, parallel = FALSE,
  n_cores = 6, model_string = NULL, set_strata_na = integer(0))

`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.
`...`	One or more unquoted expressions separated by commas, indicating the column names with the votes for each candidate.
`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`	Integer value used to set the state of the random number generator.
`parallel`	Logical value indicating whether to parallelize the models, if TRUE package parallel must be installed (uses mclapply and can not be used in Windows).
`n_cores`	If parallelizing, the number of cores to use, parameter is used in `mclapply`, `mclapply`
`model_string`	String indicating the model to be used, if NULL defaults to `"model_bern_t"`, also available `"model_t"`.
`set_strata_na`	Option to exclude strata when fitting the model, used for model evaluation and calibration.

A list with the object fitted using R2jags::jags and a data.frame with the estimation summary (posterior means, medians, standard deviations and probability intervals per party).

mrp_party_estimation

data("gto_2012")
est_gto <- mrp_estimation(gto_2012, party = pri_pvem:otros, stratum = distrito_loc_17,
  frac = 0.01, seed = 2212)
est_gto$post_summary