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Gibbs sampler for probit models

Source: R/RcppExports.R
gibbs_sampler.Rd

Gibbs sampler for probit models

Usage

gibbs_sampler(
  sufficient_statistics,
  prior,
  latent_classes,
  fixed_parameter,
  R,
  B,
  print_progress,
  ordered,
  ranked,
  save_beta_draws = FALSE
)

Arguments

sufficient_statistics

[list]
The output of sufficient_statistics.

prior

[list]
A named list of parameters for the prior distributions. See the documentation of check_prior for details about which parameters can be specified.

latent_classes

[list() | NULL]
Optionally parameters specifying the number of latent classes and their updating scheme. The values in brackets are the default.

  • C (1): The fixed number (greater or equal 1) of (initial) classes.

  • wb_update (FALSE): Set to TRUE for weight-based class updates.

  • dp_update (FALSE): Set to TRUE for Dirichlet process class updates.

  • Cmax (10): The maximum number of latent classes.

The following specifications are used for the weight-based updating scheme:

  • buffer (50): The number of iterations to wait before the next update.

  • epsmin (0.01): The threshold weight for removing a latent class.

  • epsmax (0.7): The threshold weight for splitting a latent class.

  • deltamin (0.1): The minimum mean distance before merging two classes.

  • deltashift (0.5): The scale for shifting the class means after a split.

fixed_parameter

[list]
A named list with fixed parameter values for alpha, C, s, b, Omega, Sigma, Sigma_full, beta, z, or d for the simulation.

See the vignette on model definition for definitions of these variables.

R

[integer(1)]
The number of iterations of the Gibbs sampler.

B

[integer(1)]
The length of the burn-in period.

print_progress

[logical(1)]
Print the Gibbs sampler progress?

ordered

[logical(1)]
If TRUE, the choice set alternatives is assumed to be ordered from worst to best.

ranked

[logical(1)]
Are the alternatives ranked?

save_beta_draws

[logical(1)]
Save draws for decider-specific coefficient vectors? Usually not recommended, as it requires a lot of storage space.

Value

A list of Gibbs samples for

  • Sigma,

  • alpha (only if P_f > 0),

  • s, z, b, Omega (only if P_r > 0),

  • d (only if ordered = TRUE),

and a vector class_sequence of length R, where the r-th entry is the number of classes after iteration r.

Details

This function is not supposed to be called directly, but rather via fit_model.