[DATALAD] Recorded changes

code/models/blocks/confusion_inverse_model_binomial.stan

@@ -1,4 +1,4 @@
-real inverse_model_lpmf(array[] int children,
+real inverse_model_lpdf(array [] matrix actual_confusion,
     int start, int end,
     int n_recs,
     int n_classes,
@@ -6,7 +6,6 @@ real inverse_model_lpmf(array[] int children,
     array [,] int vocs,
     array [] real age,
     matrix truth_vocs,
-    array [] matrix actual_confusion,
     //array [] vector actual_fp_rate,
     matrix mus,
     matrix etas//,
@@ -21,10 +20,10 @@ real inverse_model_lpmf(array[] int children,
             expect = rep_vector(0, 4);
 
             for (i in 1:n_classes) {
-                ll += beta_proportion_lpdf(actual_confusion[k,i] | mus[i,:], etas[i,:]);
+                ll += beta_proportion_lpdf(actual_confusion[k-start+1,i] | mus[i,:], etas[i,:]);
                 //ll += gamma_lpdf(actual_fp_rate[k] | alphas_fp, alphas_fp./mus_fp);
                 
-                expect[i] = dot_product(truth_vocs[k,:], actual_confusion[k,:,i].*(1-actual_confusion[k,:,i]));
+                expect[i] = dot_product(truth_vocs[k,:], actual_confusion[k-start+1,:,i].*(1-actual_confusion[k-start+1,:,i]));
                 //expect[i] += actual_fp_rate[k,i] * duration;
             }
             

code/models/dev_siblings_binomial.stan

@@ -103,11 +103,11 @@ parameters {
 model {
     // inverse confusion model
     target += reduce_sum(
-       inverse_model_lpmf, children, 1,
+       inverse_model_lpdf, actual_confusion_baseline, 1,
        n_recs, n_classes, recs_duration,
        vocs, age,
-       truth_vocs, actual_confusion_baseline, mus, etas//, mus_fp, etas_fp
-    );    
+       truth_vocs, mus, etas//, mus_fp, etas_fp
+    );
 
     // contribution of full recordings to the model of behavior
     #include "blocks/behavior_observations_model.stan"