• Speaker: Dr Barrie Stokes, School of Medicine and Public Health, The University of Newcastle
  • Title: Nested Sampling and its "Central Problem"
  • Location: Room V105, Mathematics Building (Callaghan Campus) The University of Newcastle
  • Time and Date: 3:00 pm, Fri, 29th Apr 2016
  • Abstract:

    Nested Sampling (NS) is a numerical algorithm for fitting models to data in the Bayesian setting, put forward by John Skilling in 2004. It has some advantages over Markov chain Monte Carlo algorithms; no starting point issues, no burn-in, no proposal distributions.

    Nested Sampling calculates the Evidence Pr[data|I] directly; posterior samples are in some sense a by-product.

    The "central problem" is the drawing of a likelihood-restricted prior sample at each compression step.

    Consideration of new such sampling methods has led to some work on equidistribution testing.

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