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PGAS errors out when adpting for nonlinear time series example #77
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Fixed some typos in the model and one in the code (variance was used instead of standard deviation in measurement model). Added PGAS sampling at the end to show that it solves the degeneracy problem, which should close the issue TuringLang#77
Apologies for the delay I was travelling. I suspect you need to change your model type to an |
Thanks for the reply! that does fix that portion. One of the things that I found really helpful about this particular tutorial (compared to say the GP one) was that it showed how to describe a model that allows for more complicated processes. That seems to have been removed in #79 because |
* Update script.jl Fixed some typos in the model and one in the code (variance was used instead of standard deviation in measurement model). Added PGAS sampling at the end to show that it solves the degeneracy problem, which should close the issue #77 * Update script.jl added back the rng argument when sampling with PG. * Update examples/particle-gibbs/script.jl Co-authored-by: FredericWantiez <frederic.wantiez@gmail.com> --------- Co-authored-by: FredericWantiez <frederic.wantiez@gmail.com>
Working through this example, and it suggests using PGAS to help with sample impoverishment. I've tried only replacing
pgas = AdvancedPS.PG(n_particles)
withpgas = AdvancedPS.PGAS(n_particles)
as is done here , while keeping all else the same but am met with this errorcould someone help with how to resolve this?
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