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statisticsdistributionpymcmcmc

What is meant by "Tuning of step methods" in pymc

I am trying to experiment with different values for the arguments of MCMC.sample in pymc.

I looked at help pages for MCMC.sample and I found:

tune_interval : int

Step methods will be tuned at intervals of this many iterations, default 1000

What does this mean by "Tuning of step methods" ? So, I don't know whether keeping this number high or low will yield me better result .

Solution

  • Tuning is an adaptive procedure for optimizing the variance of the proposal distribution with the Metropolis sampler. You definitely want to tune. I don't change my tuning interval at all, but there are scenarios where it might help, I suppose.