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Motivation for parameter clipping #19

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superbobry opened this issue May 6, 2016 · 1 comment
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Motivation for parameter clipping #19

superbobry opened this issue May 6, 2016 · 1 comment
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@superbobry
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I've been reading idr sources to complement my understanding of the paper by Li et al. One thing that caught my attention is predefined parameter ranges ranges in __init__.py. The paper doesn't mention any restrictions, so I would appreciate it if you could comment on why these are required and how the ranges were chosen for each parameter?

@superbobry superbobry changed the title Motivation for parameter ranges Motivation for parameter clipping May 6, 2016
@nboley
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nboley commented May 6, 2016

There's an identifiability problem in the model. For example, if unconstrained the sd can go to zero, which is effectively the same as the mixture parameter going to 0. I added the constraints to prevent this behavior. If the fit value is at the boundaries, then the model is probably not appropriate. Do you have examples or is the question academic?

@nboley nboley added the question label May 6, 2016
@nboley nboley closed this as completed May 24, 2016
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