Hi! I have run a SimulatedABCSMC inference using a given threshold schedule, for instance
threshold_schedule = [3.0, 2.0, 1.0, 0.5, 0.2]
Now, after checking my posterior distributions, I believe I could get better results by continuing the inference process with smaller thresholds, say
threshold_schedule = [0.1, 0.05]
Is there a way to continue the inference from the latest posterior distributions using only the two new thresholds [0.1, 0.05], without restarting the whole process from the beginning using [3.0, 2.0, 1.0, 0.5, 0.2, 0.1, 0.05] ?
It would save me a lot of time.
Thanks for your help!
Best,
Simon
I guess one option would be to use the output of the first stage as the prior for the second stage. You would most likely need to dig into internals of the package for the sampling code.
Hi! I have run a SimulatedABCSMC inference using a given threshold schedule, for instance
threshold_schedule = [3.0, 2.0, 1.0, 0.5, 0.2]
Now, after checking my posterior distributions, I believe I could get better results by continuing the inference process with smaller thresholds, saythreshold_schedule = [0.1, 0.05]
Is there a way to continue the inference from the latest posterior distributions using only the two new thresholds [0.1, 0.05], without restarting the whole process from the beginning using [3.0, 2.0, 1.0, 0.5, 0.2, 0.1, 0.05] ? It would save me a lot of time. Thanks for your help! Best, Simon