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Implementations of single and multi-ellipsoid nested sampling
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README.md

NestedSamplers.jl

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Primary Author: Miles Lucas (@mileslucas)

This package was heavily influenced by nestle and NestedSampling.jl.

TODO

  • Single Ellipsoidal sampler
  • Multi Ellipsoidal sampler
  • AbstractMCMC interface
  • Turing Interface (probably within Turing)
  • Tests
  • Optimization

Control Flow

  • Get samples from unit cube
  • Transform from unit cube to prior space
  • evaluate log likelihood at each point
  • Find lowest likelihood point
  • update evidence and information
  • add worst object to samples
  • For the Single method
    • Calculate bounding ellipsoid in prior space enlarged by some factor
    • Choose point within ellipsoid until it has likelihood greater than previous lowest likelihood
  • For the Multi method
    • Calculate largest bounding ellipsoid in prior space
    • Find the endpoints of the major axis
    • do K-means clustering with K=2 centered on the endpoints of the major axis
    • Fit ellipsoids to each cluster
    • If the volume of both ellipsoids is less than half the parent's volume, recurse into each
    • Else, return the current parent ellipsoid
    • Then, sample within the group of ellipsoids until finding a point with greater likelihood than the previous lowest
  • The final N-nactive points just add the current active points to sample list (no longer fitting ellipsoids)
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