sample_pum_static {pumBayes}R Documentation

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
)

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'.

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.

Examples


# 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)


[Package pumBayes version 1.0.0 Index]