pyhrf.jde.nrl.ar.NRLARSampler(do_sampling=True, val_ini=None, contrasts={}, do_label_sampling=True, use_true_nrls=False, use_true_labels=False, labels_ini=None, ppm_proba_threshold=0.05, ppm_value_threshold=0, ppm_value_multi_threshold=array([ 0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1., 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2., 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3., 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. ]), mean_activation_threshold=4, rescale_results=False, wip_variance_computation=False)¶Bases: pyhrf.jde.nrl.bigaussian.NRLSampler
Class handling the Gibbs sampling of Neural Response Levels according to:
Makni, S., Ciuciu, P., Idier, J., & Poline, J. (2006). Joint Detection-Estimation of Brain Activity in fMRI using an Autoregressive Noise Model. In 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006. (pp. 1048–1051). IEEE. https://doi.org/10.1109/ISBI.2006.1625101
Inherits the abstract class C{ GibbsSamplerVariable}.
cleanMemory()¶computeMeanVarClassApost(j, variables)¶computeVarYTilde(varXh, varMBYPl)¶linkToData(dataInput)¶sampleNextAlt(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated.
sampleNextInternal(variables)¶Define the behaviour of the variable at each sampling step when its sampling is not activated. Must be overriden in child classes.
samplingWarmUp(variables)¶#TODO : comment