diff --git a/BayesianKDEy/full_experiments.py b/BayesianKDEy/full_experiments.py
index e592214..82876c6 100644
--- a/BayesianKDEy/full_experiments.py
+++ b/BayesianKDEy/full_experiments.py
@@ -10,7 +10,7 @@ from copy import deepcopy as cp
 import quapy as qp
 from BayesianKDEy._bayeisan_kdey import BayesianKDEy
 from build.lib.quapy.data import LabelledCollection
-from quapy.method.aggregative import DistributionMatchingY as DMy, AggregativeQuantifier
+from quapy.method.aggregative import DistributionMatchingY as DMy, AggregativeQuantifier, EMQ
 from quapy.method.base import BinaryQuantifier, BaseQuantifier
 from quapy.model_selection import GridSearchQ
 from quapy.data import Dataset
@@ -54,6 +54,7 @@ def methods():
         quantifier with optimized hyperparameters
     """
     acc_hyper = {}
+    emq_hyper = {'calib': [None, 'nbvs', 'bcts', 'ts', 'vs']}
     hdy_hyper = {'nbins': [3,4,5,8,16,32]}
     kdey_hyper = {'bandwidth': [0.001, 0.005, 0.01, 0.05, 0.1, 0.2]}
     kdey_hyper_clr = {'bandwidth': [0.05, 0.1, 0.5, 1., 2., 5.]}
@@ -65,6 +66,8 @@ def methods():
     yield 'BootstrapACC', ACC(LR()), acc_hyper, lambda hyper: AggregativeBootstrap(ACC(LR()), n_test_samples=1000, random_state=0), multiclass_method
     yield 'BayesianACC', ACC(LR()), acc_hyper, lambda hyper: BayesianCC(LR(), mcmc_seed=0), multiclass_method
 
+    yield 'BootstrapEMQ', EMQ(LR(), on_calib_error='backup'), emq_hyper, lambda hyper: AggregativeBootstrap(EMQ(LR(), on_calib_error='backup'), n_test_samples=1000, random_state=0), multiclass_method
+
     yield 'BootstrapHDy', DMy(LR()), hdy_hyper, lambda hyper: AggregativeBootstrap(DMy(LR(), **hyper), n_test_samples=1000, random_state=0), multiclass_method
     yield 'BayesianHDy', DMy(LR()), hdy_hyper, lambda hyper: PQ(LR(), stan_seed=0, **hyper), only_binary