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Time-varying parameters (i.e. conversion to latent variables) #600

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sbfnk opened this issue Mar 6, 2024 · 2 comments
Open

Time-varying parameters (i.e. conversion to latent variables) #600

sbfnk opened this issue Mar 6, 2024 · 2 comments

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@sbfnk
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sbfnk commented Mar 6, 2024

Once #504 and #525 are done this opens the option of extending the distribution interface to allow any parameter to vary over time. An interface for Gaussian processes could e.g. look like

delay <- GP(mean = Normal(mean = 5, sd = 1))

for mean reverting GPs or

delay <- GP(init = Normal(mean = 5, sd = 1))

for GPs on first differences

A similar interface could be created for random walks (RW).

@sbfnk
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sbfnk commented Mar 6, 2024

Would require quite a few changes to the underlying model(s) as PMFs would turn from vectors into matrices.

@seabbs
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seabbs commented Mar 6, 2024

We should have a chat at some point because this is feeling like interface -> internal vs epinowcast internals -> interface (i.e replicating the same functionality but in the other direction.

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