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Parameter Object and Adaptation #16

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LeahPrice opened this Issue Aug 4, 2017 · 3 comments

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LeahPrice commented Aug 4, 2017

The next couple of planned pull requests are about making it easier to keep track of and adapt additional algorithm parameters. This is useful in general and it is especially important when using SMC to perform inference on static Bayesian models. In this pull request, I'd like to make the necessary changes to the existing library:

  • Adding a template parameter for the algorithm parameters to the sampler object
  • Creating a base class for adaptation

My plan is to give the examples in a separate pull request.

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adamjohansen Aug 4, 2017

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This seems sensible to me.

If I interpret this correctly, the additional template parameter will break backward compatibility; that should be clearly signposted in the associated docs.

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adamjohansen commented Aug 4, 2017

This seems sensible to me.

If I interpret this correctly, the additional template parameter will break backward compatibility; that should be clearly signposted in the associated docs.

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LeahPrice Aug 4, 2017

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I've set it up so that there is a empty class as the default template parameter, so fortunately it shouldn't break backwards compatibility.

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LeahPrice commented Aug 4, 2017

I've set it up so that there is a empty class as the default template parameter, so fortunately it shouldn't break backwards compatibility.

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adamjohansen Aug 4, 2017

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Oh, great -- I'd forgotten where we'd ended up after all those discussions. I should have checked...

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adamjohansen commented Aug 4, 2017

Oh, great -- I'd forgotten where we'd ended up after all those discussions. I should have checked...

@LeahPrice LeahPrice closed this Aug 8, 2017

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