pyhrf.jde.noise module¶
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class
pyhrf.jde.noise.NoiseARParamsSampler(do_sampling=True, use_true_value=False, val_ini=None)¶ Bases:
pyhrf.xmlio.Initable,pyhrf.jde.samplerbase.GibbsSamplerVariable-
MH_ARsampling_gauss_proposal(sig2, M)¶
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MH_ARsampling_optim(A, reps, M)¶
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P_SAMPLE_FLAG= 'sampleFlag'¶
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P_USE_TRUE_VALUE= 'useTrueValue'¶
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P_VAL_INI= 'initialValue'¶
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checkAndSetInitValue(variables)¶
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computeInvAutoCorrNoise(ARp)¶
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defaultParameters= {'useTrueValue': False, 'initialValue': None, 'sampleFlag': True}¶
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finalizeSampling()¶
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linkToData(dataInput)¶
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sampleNextInternal(variables)¶
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class
pyhrf.jde.noise.NoiseVarianceARSampler(do_sampling=True, use_true_value=False, val_ini=None)¶ Bases:
pyhrf.jde.noise.NoiseVarianceSampler-
checkAndSetInitValue(variables)¶
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computeVarYTilde(varNrls, varXh, varMBYPl)¶
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finalizeSampling()¶
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sampleNextInternal(variables)¶
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class
pyhrf.jde.noise.NoiseVarianceSampler(do_sampling=True, use_true_value=False, val_ini=None)¶ Bases:
pyhrf.xmlio.Initable,pyhrf.jde.samplerbase.GibbsSamplerVariable#TODO : comment
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checkAndSetInitValue(variables)¶
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computeMXhQXh(h, varXQX)¶
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compute_aaXhQXhi(aa, i)¶
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finalizeSampling()¶
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linkToData(dataInput)¶
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sampleNextInternal(variables)¶
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sampleNextInternal_bak(variables)¶
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class
pyhrf.jde.noise.NoiseVarianceSamplerWithRelVar(do_sampling=True, use_true_value=False, val_ini=None)¶ Bases:
pyhrf.jde.noise.NoiseVarianceSampler-
computeWW(w, destww)¶
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compute_aawwXhQXhi(ww, aa, i)¶
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finalizeSampling()¶
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sampleNextInternal(variables)¶
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class
pyhrf.jde.noise.NoiseVariance_Drift_Sampler(do_sampling=True, use_true_value=False, val_ini=None)¶ Bases:
pyhrf.xmlio.Initable,pyhrf.jde.samplerbase.GibbsSamplerVariable-
checkAndSetInitValue(variables)¶
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linkToData(dataInput)¶
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sampleNextInternal(variables)¶
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class
pyhrf.jde.noise.NoiseVariancewithHabSampler(do_sampling=True, use_true_value=False, val_ini=None)¶ Bases:
pyhrf.jde.noise.NoiseVarianceSampler#TODO : Sampling procedure for noise variance parameters (white noise) #in case of habituation modeling wrt magnitude
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finalizeSampling()¶
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sampleNextInternal(variables)¶
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