dynesty: a dynamic nested sampling package for estimating Bayesian posteriors and evidences
نویسندگان
چکیده
منابع مشابه
Discussion of Nested Sampling for Bayesian Computations
We comment on several aspects of Skilling's paper presented at Valencia 8. In particular we prove the convergence in probability of the algorithm for a wide class of situations, comment on its potential utility and discuss aspects where further work is needed to assess the approach.
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Nested sampling estimates directly how the likelihood function relates to prior mass. The evidence (alternatively the marginal likelihood, marginal density of the data, or the prior predictive) is immediately obtained by summation. It is the prime result of the computation, and is accompanied by an estimate of numerical uncertainty. Samples from the posterior distribution are an optional byprod...
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The ingredients to a Bayesian analysis comprise the sampling model {Pθ : θ ∈ Ω} for the response X, the prior Π for the parameter θ, and the observed value X = x. This is equivalent to specifying the joint model Pθ ×Π for (X, θ) and the observed value X = x. In many situations we may also have a loss function but we ignore this here as it is not material to our discussion. We refer to Pθ ×Π as ...
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We study how much data a Bayesian observer needs to correctly infer the relative likelihoods of two events when both events are arbitrarily rare. Each period, either a blue die or a red die is tossed. The two dice land on side [Formula: see text] with unknown probabilities [Formula: see text] and [Formula: see text], which can be arbitrarily low. Given a data-generating process where [Formula: ...
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ژورنال
عنوان ژورنال: Monthly Notices of the Royal Astronomical Society
سال: 2020
ISSN: 0035-8711,1365-2966
DOI: 10.1093/mnras/staa278