pumBayes (version 1.0.2)

sample_pum_static: Generate posterior samples from the static probit unfolding model

Description

This function generates posterior samples of all parameters based on the static probit unfolding model.

Usage

sample_pum_static(
  vote_info,
  hyperparams,
  control,
  pos_leg = 0,
  verbose = FALSE,
  pre_run = NULL,
  appended = FALSE
)

Value

A list primarily containing: - `beta`: A matrix of posterior samples for `beta`. - `alpha1`: A matrix of posterior samples for `alpha1`. - `alpha2`: A matrix of posterior samples for `alpha2`. - `delta1`: A matrix of posterior samples for `delta1`. - `delta2`: A matrix of posterior samples for `delta2`. - `vote_info`: The input vote object.

Arguments

vote_info

A logical vote matrix (or a rollcall object) in which rows represent members and columns represent issues.

hyperparams

A list of hyperparameter values: - `beta_mean`: Prior mean for beta. - `beta_var`: Variance of beta. - `alpha_mean`: A vector of two components representing the prior means of `alpha1` and `alpha2`. - `alpha_scale`: Scale parameter for `alpha1` and `alpha2`. - `delta_mean`: A vector of two components representing the prior means of `delta1` and `delta2`. - `delta_scale`: Scale parameter for `delta1` and `delta2`.

control

A list of MCMC configurations: - `num_iter`: Total number of iterations. It is recommended to set this to at least 30,000 to ensure reliable results. - `burn_in`: The number of initial iterations to discard as part of the burn-in period before retaining samples. - `keep_iter`: Interval at which iterations are kept for posterior samples. - `flip_rate`: Probability of directly flipping signs in the M-H step, rather than resampling from the priors.

pos_leg

Name of the legislator whose position is kept positive.

verbose

Logical. If `TRUE`, prints progress and additional information during the sampling process.

pre_run

A list containing the output from a previous run of the function. If provided, the last iteration of the previous run will be used as the initial point of the new run. Defaults to `NULL`.

appended

Logical. If `TRUE`, the new samples will be appended to the samples from the previous run. Defaults to `FALSE`.

Examples

# \donttest{
# Long-running example
data(h116)
h116.c = preprocess_rollcall(h116)
hyperparams <- list(beta_mean = 0, beta_var = 1, alpha_mean = c(0, 0),
                    alpha_scale = 5, delta_mean = c(-2, 10), delta_scale = sqrt(10))
control <- list(num_iter = 2, burn_in = 0, keep_iter = 1, flip_rate = 0.1)
h116.c.pum <- sample_pum_static(h116.c, hyperparams,
                                  control, pos_leg = grep("SCALISE", rownames(h116.c$votes)),
                                  verbose = FALSE, pre_run = NULL, appended = FALSE)
# }