Small change for naming consistency

MaartenMarsman · MaartenMarsman · commit e008ffd8e765 · 2025-09-21T20:38:36.000+02:00
diff --git a/R/RcppExports.R b/R/RcppExports.R
@@ -5,8 +5,8 @@ run_bgmCompare_parallel <- function(observations, num_groups, counts_per_categor
     .Call(`_bgms_run_bgmCompare_parallel`, observations, num_groups, counts_per_category, blume_capel_stats, pairwise_stats, num_categories, main_alpha, main_beta, pairwise_scale, difference_scale, difference_selection_alpha, difference_selection_beta, difference_prior, iter, burnin, na_impute, missing_data_indices, is_ordinal_variable, baseline_category, difference_selection, main_effect_indices, pairwise_effect_indices, target_accept, nuts_max_depth, learn_mass_matrix, projection, group_membership, group_indices, interaction_index_matrix, inclusion_probability, num_chains, nThreads, seed, update_method, hmc_num_leapfrogs)
 }
 
-run_bgm_parallel <- function(observations, num_categories, interaction_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed) {
-    .Call(`_bgms_run_bgm_parallel`, observations, num_categories, interaction_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed)
+run_bgm_parallel <- function(observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed) {
+    .Call(`_bgms_run_bgm_parallel`, observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed)
 }
 
 sample_omrf_gibbs <- function(no_states, no_variables, no_categories, interactions, thresholds, iter) {
diff --git a/R/bgm.R b/R/bgm.R
@@ -503,7 +503,7 @@ bgm = function(
 
   out = run_bgm_parallel(
     observations = x, num_categories = num_categories,
-    interaction_scale = interaction_scale, edge_prior = edge_prior,
+    pairwise_scale = interaction_scale, edge_prior = edge_prior,
     inclusion_probability = inclusion_probability,
     beta_bernoulli_alpha = beta_bernoulli_alpha,
     beta_bernoulli_beta = beta_bernoulli_beta,
diff --git a/R/bgmCompare.R b/R/bgmCompare.R
@@ -78,7 +78,7 @@ bgmCompare = function(
     x,
     y,
     group_indicator,
-    difference_selection = FALSE,
+    difference_selection = TRUE,
     variable_type = "ordinal",
     baseline_category,
     difference_scale = 1,
diff --git a/man/bgmCompare.Rd b/man/bgmCompare.Rd
diff --git a/src/RcppExports.cpp b/src/RcppExports.cpp
@@ -57,14 +57,14 @@ BEGIN_RCPP
 END_RCPP
 }
 // run_bgm_parallel
-Rcpp::List run_bgm_parallel(const arma::imat& observations, const arma::ivec& num_categories, double interaction_scale, const std::string& edge_prior, const arma::mat& inclusion_probability, double beta_bernoulli_alpha, double beta_bernoulli_beta, double dirichlet_alpha, double lambda, const arma::imat& interaction_index_matrix, int iter, int burnin, const arma::imat& counts_per_category, const arma::imat& blume_capel_stats, double main_alpha, double main_beta, bool na_impute, const arma::imat& missing_index, const arma::uvec& is_ordinal_variable, const arma::ivec& baseline_category, bool edge_selection, const std::string& update_method, const arma::imat& pairwise_effect_indices, double target_accept, const arma::imat& pairwise_stats, int hmc_num_leapfrogs, int nuts_max_depth, bool learn_mass_matrix, int num_chains, int nThreads, uint64_t seed);
-RcppExport SEXP _bgms_run_bgm_parallel(SEXP observationsSEXP, SEXP num_categoriesSEXP, SEXP interaction_scaleSEXP, SEXP edge_priorSEXP, SEXP inclusion_probabilitySEXP, SEXP beta_bernoulli_alphaSEXP, SEXP beta_bernoulli_betaSEXP, SEXP dirichlet_alphaSEXP, SEXP lambdaSEXP, SEXP interaction_index_matrixSEXP, SEXP iterSEXP, SEXP burninSEXP, SEXP counts_per_categorySEXP, SEXP blume_capel_statsSEXP, SEXP main_alphaSEXP, SEXP main_betaSEXP, SEXP na_imputeSEXP, SEXP missing_indexSEXP, SEXP is_ordinal_variableSEXP, SEXP baseline_categorySEXP, SEXP edge_selectionSEXP, SEXP update_methodSEXP, SEXP pairwise_effect_indicesSEXP, SEXP target_acceptSEXP, SEXP pairwise_statsSEXP, SEXP hmc_num_leapfrogsSEXP, SEXP nuts_max_depthSEXP, SEXP learn_mass_matrixSEXP, SEXP num_chainsSEXP, SEXP nThreadsSEXP, SEXP seedSEXP) {
+Rcpp::List run_bgm_parallel(const arma::imat& observations, const arma::ivec& num_categories, double pairwise_scale, const std::string& edge_prior, const arma::mat& inclusion_probability, double beta_bernoulli_alpha, double beta_bernoulli_beta, double dirichlet_alpha, double lambda, const arma::imat& interaction_index_matrix, int iter, int burnin, const arma::imat& counts_per_category, const arma::imat& blume_capel_stats, double main_alpha, double main_beta, bool na_impute, const arma::imat& missing_index, const arma::uvec& is_ordinal_variable, const arma::ivec& baseline_category, bool edge_selection, const std::string& update_method, const arma::imat& pairwise_effect_indices, double target_accept, const arma::imat& pairwise_stats, int hmc_num_leapfrogs, int nuts_max_depth, bool learn_mass_matrix, int num_chains, int nThreads, uint64_t seed);
+RcppExport SEXP _bgms_run_bgm_parallel(SEXP observationsSEXP, SEXP num_categoriesSEXP, SEXP pairwise_scaleSEXP, SEXP edge_priorSEXP, SEXP inclusion_probabilitySEXP, SEXP beta_bernoulli_alphaSEXP, SEXP beta_bernoulli_betaSEXP, SEXP dirichlet_alphaSEXP, SEXP lambdaSEXP, SEXP interaction_index_matrixSEXP, SEXP iterSEXP, SEXP burninSEXP, SEXP counts_per_categorySEXP, SEXP blume_capel_statsSEXP, SEXP main_alphaSEXP, SEXP main_betaSEXP, SEXP na_imputeSEXP, SEXP missing_indexSEXP, SEXP is_ordinal_variableSEXP, SEXP baseline_categorySEXP, SEXP edge_selectionSEXP, SEXP update_methodSEXP, SEXP pairwise_effect_indicesSEXP, SEXP target_acceptSEXP, SEXP pairwise_statsSEXP, SEXP hmc_num_leapfrogsSEXP, SEXP nuts_max_depthSEXP, SEXP learn_mass_matrixSEXP, SEXP num_chainsSEXP, SEXP nThreadsSEXP, SEXP seedSEXP) {
 BEGIN_RCPP
     Rcpp::RObject rcpp_result_gen;
     Rcpp::RNGScope rcpp_rngScope_gen;
     Rcpp::traits::input_parameter< const arma::imat& >::type observations(observationsSEXP);
     Rcpp::traits::input_parameter< const arma::ivec& >::type num_categories(num_categoriesSEXP);
-    Rcpp::traits::input_parameter< double >::type interaction_scale(interaction_scaleSEXP);
+    Rcpp::traits::input_parameter< double >::type pairwise_scale(pairwise_scaleSEXP);
     Rcpp::traits::input_parameter< const std::string& >::type edge_prior(edge_priorSEXP);
     Rcpp::traits::input_parameter< const arma::mat& >::type inclusion_probability(inclusion_probabilitySEXP);
     Rcpp::traits::input_parameter< double >::type beta_bernoulli_alpha(beta_bernoulli_alphaSEXP);
@@ -93,7 +93,7 @@ BEGIN_RCPP
     Rcpp::traits::input_parameter< int >::type num_chains(num_chainsSEXP);
     Rcpp::traits::input_parameter< int >::type nThreads(nThreadsSEXP);
     Rcpp::traits::input_parameter< uint64_t >::type seed(seedSEXP);
-    rcpp_result_gen = Rcpp::wrap(run_bgm_parallel(observations, num_categories, interaction_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed));
+    rcpp_result_gen = Rcpp::wrap(run_bgm_parallel(observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed));
     return rcpp_result_gen;
 END_RCPP
 }
diff --git a/src/bgm_logp_and_grad.cpp b/src/bgm_logp_and_grad.cpp
@@ -2,6 +2,7 @@
 #include "bgm_helper.h"
 #include "bgm_logp_and_grad.h"
 #include "common_helpers.h"
+
 using namespace Rcpp;
 
 
@@ -145,7 +146,7 @@ double log_pseudoposterior_main_effects_component (
  *  - inclusion_indicator: Symmetric binary matrix of active pairwise effects.
  *  - is_ordinal_variable: Indicator (1 = ordinal, 0 = Blume–Capel).
  *  - baseline_category: Reference categories for Blume–Capel variables.
- *  - interaction_scale: Scale parameter of the Cauchy prior on interactions.
+ *  - pairwise_scale: Scale parameter of the Cauchy prior on interactions.
  *  - pairwise_stats: Sufficient statistics for pairwise counts.
  *  - var1, var2: Indices of the variable pair being updated.
  *
@@ -165,7 +166,7 @@ double log_pseudoposterior_interactions_component (
     const arma::imat& inclusion_indicator,
     const arma::uvec& is_ordinal_variable,
     const arma::ivec& baseline_category,
-    const double interaction_scale,
+    const double pairwise_scale,
     const arma::imat& pairwise_stats,
     const int var1,
     const int var2
@@ -210,7 +211,7 @@ double log_pseudoposterior_interactions_component (
 
   // Add Cauchy prior terms for included pairwise effects
   if (inclusion_indicator (var1, var2) == 1) {
-    log_pseudo_posterior += R::dcauchy (pairwise_effects (var1, var2), 0.0, interaction_scale, true);
+    log_pseudo_posterior += R::dcauchy (pairwise_effects (var1, var2), 0.0, pairwise_scale, true);
   }
 
   return log_pseudo_posterior;
@@ -241,7 +242,7 @@ double log_pseudoposterior_interactions_component (
  *  - baseline_category: Reference categories for Blume–Capel variables.
  *  - is_ordinal_variable: Indicator (1 = ordinal, 0 = Blume–Capel).
  *  - main_alpha, main_beta: Hyperparameters for the Beta priors.
- *  - interaction_scale: Scale parameter of the Cauchy prior on interactions.
+ *  - pairwise_scale: Scale parameter of the Cauchy prior on interactions.
  *  - pairwise_stats: Pairwise sufficient statistics.
  *  - residual_matrix: Matrix of residual scores (persons × variables).
  *
@@ -265,7 +266,7 @@ double log_pseudoposterior (
     const arma::uvec& is_ordinal_variable,
     const double main_alpha,
     const double main_beta,
-    const double interaction_scale,
+    const double pairwise_scale,
     const arma::imat& pairwise_stats,
     const arma::mat& residual_matrix
 ) {
@@ -304,7 +305,7 @@ double log_pseudoposterior (
 
       double value = pairwise_effects(var1, var2);
       log_pseudoposterior += 2.0 * pairwise_stats(var1, var2) * value;
-      log_pseudoposterior += R::dcauchy(value, 0.0, interaction_scale, true); // Cauchy prior
+      log_pseudoposterior += R::dcauchy(value, 0.0, pairwise_scale, true); // Cauchy prior
     }
   }
 
@@ -371,7 +372,7 @@ double log_pseudoposterior (
  *  - baseline_category: Reference categories for Blume–Capel variables.
  *  - is_ordinal_variable: Indicator (1 = ordinal, 0 = Blume–Capel).
  *  - main_alpha, main_beta: Hyperparameters for Beta priors.
- *  - interaction_scale: Scale parameter of the Cauchy prior on interactions.
+ *  - pairwise_scale: Scale parameter of the Cauchy prior on interactions.
  *  - pairwise_stats: Sufficient statistics for pairwise effects.
  *  - residual_matrix: Matrix of residual scores (persons × variables).
  *
@@ -396,7 +397,7 @@ arma::vec gradient_log_pseudoposterior (
     const arma::uvec& is_ordinal_variable,
     const double main_alpha,
     const double main_beta,
-    const double interaction_scale,
+    const double pairwise_scale,
     const arma::imat& pairwise_stats,
     const arma::mat& residual_matrix
 ) {
@@ -551,7 +552,7 @@ arma::vec gradient_log_pseudoposterior (
       // ---- Gradient contribution from Cauchy prior
       int location = index_matrix(var1, var2);
       const double effect = pairwise_effects (var1, var2);
-      gradient (location) -= 2.0 * effect / (effect * effect + interaction_scale * interaction_scale);
+      gradient (location) -= 2.0 * effect / (effect * effect + pairwise_scale * pairwise_scale);
     }
   }
 
@@ -579,7 +580,7 @@ arma::vec gradient_log_pseudoposterior (
  *  - baseline_category: Reference categories for Blume–Capel variables.
  *  - is_ordinal_variable: Indicator (1 = ordinal, 0 = Blume–Capel).
  *  - main_alpha, main_beta: Hyperparameters for Beta priors.
- *  - interaction_scale: Scale parameter of the Cauchy prior on interactions.
+ *  - pairwise_scale: Scale parameter of the Cauchy prior on interactions.
  *  - pairwise_stats: Sufficient statistics for pairwise effects.
  *  - residual_matrix: Matrix of residual scores (persons × variables).
  *
@@ -603,7 +604,7 @@ arma::vec gradient_log_pseudoposterior_active (
     const arma::uvec& is_ordinal_variable,
     const double main_alpha,
     const double main_beta,
-    const double interaction_scale,
+    const double pairwise_scale,
     const arma::imat& pairwise_stats,
     const arma::mat& residual_matrix
 ) {
@@ -613,7 +614,7 @@ arma::vec gradient_log_pseudoposterior_active (
     main_effects, pairwise_effects, inclusion_indicator, observations,
     num_categories, counts_per_category, blume_capel_stats,
     baseline_category, is_ordinal_variable, main_alpha, main_beta,
-    interaction_scale, pairwise_stats, residual_matrix
+    pairwise_scale, pairwise_stats, residual_matrix
   );
 
   // Step 2: Extract compressed gradient (same layout as new vectorizer)
diff --git a/src/bgm_logp_and_grad.h b/src/bgm_logp_and_grad.h
@@ -27,7 +27,7 @@ double log_pseudoposterior_interactions_component (
     const arma::imat& inclusion_indicator,
     const arma::uvec& is_ordinal_variable,
     const arma::ivec& baseline_category,
-    const double interaction_scale,
+    const double pairwise_scale,
     const arma::imat& pairwise_stats,
     const int var1,
     const int var2
@@ -46,7 +46,7 @@ double log_pseudoposterior (
     const arma::uvec& is_ordinal_variable,
     const double main_alpha,
     const double main_beta,
-    const double interaction_scale,
+    const double pairwise_scale,
     const arma::imat& pairwise_stats,
     const arma::mat& residual_matrix
 );
@@ -64,7 +64,7 @@ arma::vec gradient_log_pseudoposterior (
     const arma::uvec& is_ordinal_variable,
     const double main_alpha,
     const double main_beta,
-    const double interaction_scale,
+    const double pairwise_scale,
     const arma::imat& pairwise_stats,
     const arma::mat& residual_matrix
 );
@@ -82,7 +82,7 @@ arma::vec gradient_log_pseudoposterior_active (
     const arma::uvec& is_ordinal_variable,
     const double main_alpha,
     const double main_beta,
-    const double interaction_scale,
+    const double pairwise_scale,
     const arma::imat& pairwise_stats,
     const arma::mat& residual_matrix
 );
diff --git a/src/bgm_parallel.cpp b/src/bgm_parallel.cpp
@@ -58,7 +58,7 @@ struct ChainResult {
 struct GibbsChainRunner : public Worker {
   const arma::imat& observations;
   const arma::ivec& num_categories;
-  double interaction_scale;
+  double  pairwise_scale;
   const std::string& edge_prior;
   const arma::mat& inclusion_probability;
   double beta_bernoulli_alpha;
@@ -94,7 +94,7 @@ struct GibbsChainRunner : public Worker {
   GibbsChainRunner(
     const arma::imat& observations,
     const arma::ivec& num_categories,
-    double interaction_scale,
+    double  pairwise_scale,
     const std::string& edge_prior,
     const arma::mat& inclusion_probability,
     double beta_bernoulli_alpha,
@@ -125,7 +125,7 @@ struct GibbsChainRunner : public Worker {
   ) :
     observations(observations),
     num_categories(num_categories),
-    interaction_scale(interaction_scale),
+     pairwise_scale( pairwise_scale),
     edge_prior(edge_prior),
     inclusion_probability(inclusion_probability),
     beta_bernoulli_alpha(beta_bernoulli_alpha),
@@ -168,7 +168,7 @@ struct GibbsChainRunner : public Worker {
           out.chain_id,
           observations,
           num_categories,
-          interaction_scale,
+           pairwise_scale,
           edge_prior,
           inclusion_probability,
           beta_bernoulli_alpha,
@@ -222,7 +222,7 @@ struct GibbsChainRunner : public Worker {
  * Inputs:
  *  - observations: Matrix of categorical observations (persons × variables).
  *  - num_categories: Number of categories per variable.
- *  - interaction_scale: Scale parameter of the Cauchy prior on pairwise effects.
+ *  -  pairwise_scale: Scale parameter of the Cauchy prior on pairwise effects.
  *  - edge_prior: Prior specification for edge inclusion.
  *  - inclusion_probability: Matrix of prior inclusion probabilities.
  *  - beta_bernoulli_alpha, beta_bernoulli_beta: Hyperparameters for Bernoulli priors.
@@ -263,7 +263,7 @@ struct GibbsChainRunner : public Worker {
 Rcpp::List run_bgm_parallel(
     const arma::imat& observations,
     const arma::ivec& num_categories,
-    double interaction_scale,
+    double  pairwise_scale,
     const std::string& edge_prior,
     const arma::mat& inclusion_probability,
     double beta_bernoulli_alpha,
@@ -302,7 +302,7 @@ Rcpp::List run_bgm_parallel(
   }
 
   GibbsChainRunner worker(
-      observations, num_categories, interaction_scale, edge_prior,
+      observations, num_categories,  pairwise_scale, edge_prior,
       inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta,
       dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin,
       counts_per_category, blume_capel_stats, main_alpha, main_beta,
diff --git a/src/bgm_sampler.cpp b/src/bgm_sampler.cpp
diff --git a/src/bgm_sampler.h b/src/bgm_sampler.h

Original file line number	Diff line number	Diff line change
`@@ -5,8 +5,8 @@ run_bgmCompare_parallel <- function(observations, num_groups, counts_per_categor`
`5`	`5`	.Call(`_bgms_run_bgmCompare_parallel`, observations, num_groups, counts_per_category, blume_capel_stats, pairwise_stats, num_categories, main_alpha, main_beta, pairwise_scale, difference_scale, difference_selection_alpha, difference_selection_beta, difference_prior, iter, burnin, na_impute, missing_data_indices, is_ordinal_variable, baseline_category, difference_selection, main_effect_indices, pairwise_effect_indices, target_accept, nuts_max_depth, learn_mass_matrix, projection, group_membership, group_indices, interaction_index_matrix, inclusion_probability, num_chains, nThreads, seed, update_method, hmc_num_leapfrogs)
`6`	`6`	`}`
`7`	`7`
`8`		-run_bgm_parallel <- function(observations, num_categories, interaction_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed) {
`9`		- .Call(`_bgms_run_bgm_parallel`, observations, num_categories, interaction_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed)
	`8`	+run_bgm_parallel <- function(observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed) {
	`9`	+ .Call(`_bgms_run_bgm_parallel`, observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed)
`10`	`10`	`}`
`11`	`11`
`12`	`12`	`sample_omrf_gibbs <- function(no_states, no_variables, no_categories, interactions, thresholds, iter) {`