pymc.smc.smc.IMH#

class pymc.smc.smc.IMH(*args, correlation_threshold=0.01, **kwargs)[source]#

Independent Metropolis-Hastings SMC kernel

Methods

IMH.__init__(*args[, correlation_threshold])

Parameters

IMH.initialize_population()

Create an initial population from the prior distribution

IMH.mutate()

Independent Metropolis-Hastings perturbation.

IMH.resample()

Resample particles based on importance weights

IMH.sample_settings()

Kernel settings to be saved once at the end of sampling

IMH.sample_stats()

Stats to be saved at the end of each stage

IMH.setup_kernel()

Setup logic performed once before sampling starts

IMH.tune()

Tuning logic performed before every mutation step

IMH.update_beta_and_weights()

Calculate the next inverse temperature (beta)