neuroprob/likelihoods.py
def eval_dispersion_mapping(self, XZ, samples, neuron):
        """
        Posterior predictive mean of the dispersion model.
        """
        disp, disp_var = self.dispersion_mapping.compute_F(XZ)
        dh = self.mc_gen(disp, disp_var, samples, neuron)
        return self.dispersion_mapping.f(dh).mean(0)

        Posterior predictive mean of the dispersion model.
        
Posterior predictive mean of the dispersion model.
Posterior predictive mean of the dispersion model .
def eval_dispersion_mapping(self, XZ, samples, neuron):
        disp, disp_var = self.dispersion_mapping.compute_F(XZ)
        dh = self.mc_gen(disp, disp_var, samples, neuron)
        return self.dispersion_mapping.f(dh).mean(0)
def eval_dispersion_mapping ( self , XZ , samples , neuron ) : disp , disp_var = self . dispersion_mapping . compute_F ( XZ ) dh = self . mc_gen ( disp , disp_var , samples , neuron ) return self . dispersion_mapping . f ( dh ) . mean ( 0 )
Posterior predictive mean of the dispersion model.
Posterior predictive mean of the dispersion model .
"""
        Posterior predictive mean of the dispersion model.
        """
self
XZ
samples
neuron