8000 Integrate multi-stage follow-up Bayes factor functionalities into PyFstat · Issue #333 · PyFstat/PyFstat · GitHub
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Rodrigo-Tenorio opened this issue Oct 4, 2021 · 0 comments
Open
1 of 11 tasks

Integrate multi-stage follow-up Bayes factor functionalities into PyFstat #333

Rodrigo-Tenorio opened this issue Oct 4, 2021 · 0 comments
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followup related to follow-up codes grids issues with the grid-based searches mcmc issues with the mcmc-based searches

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@Rodrigo-Tenorio
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Rodrigo-Tenorio commented Oct 4, 2021 •
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Tenorio, Keitel, Sintes (2021) introduces a new Bayes factor to evaluate the multi-stage follow-up of a CW candidate. The following items should be addressed in order to fully implement this new functionality into PyFstat:

  • Overhaul MCMCFollowUpSearch and create a new class BstarSN:

    • Re-purpose not do duplicate Coherent and Semicoherent MCMC searches.
    • Uncouple and clean up coherence-time ladder computation.
    • Add prior class (or similar) to parse posterior samples from previous stages to setup priors.

  • Implement noise-hypothesis functions into BstarSN:

    • Implement off-sourcing (maybe it's simpler to use CFSv2's input grid functionality ? )
    • Implement Gumbel fit.

  • Implement signal-hypothesis functions into BstarSN:

    • Re-compute 2F at different stages using the loudest candidate from the last one.
    • Implement 2F -> rho -> 2F integral with numerical checks.

  • Add reference to README Update README with multi-stage follow-up methods paper #332
@Rodrigo-Tenorio Rodrigo-Tenorio added grids issues with the grid-based searches mcmc issues with the mcmc-based searches followup related to follow-up codes labels Oct 4, 2021
@dbkeitel dbkeitel mentioned this issue Oct 22, 2021
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