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BEAST HackDay MegaBEAST (27 Nov 2017)

Karl Gordon
November 27, 2017

BEAST HackDay MegaBEAST (27 Nov 2017)

Karl Gordon

November 27, 2017
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  1. BEAST Math • Bayes’ Theorem – P(A|B) = P(B|A)P(A)/P(B) •

    P(θ|d) = P(d|θ)P(θ)/P(d) – θ = BEAST model parameters • Age, mass, metallicity, A(V), R(V), f A , distance • Observation model parameters: source density – d = data (fluxes) – P(θ) = priors – P(d) = 1 (??)
  2. MegaBEAST Math • P(θ|d) = P(d|θ)P(θ) = BEAST output •

    P(φ|d) = product[ int i { P(φ|θ)C(θ)(P(θ|d) i } ] – φ = MegaBEAST parameters • “meta” parameters • Star formation vs time, IMF, mass-metallicity, • log-normal parameters for A(V), R(V), f A • Distance function (Gaussian with width?) – P(φ|θ) = P(θ|φ)P(φ)/P(θ) = MegaBEAST computation • Adjustable priors • P(θ) = 1 (??) – C(θ) = completeness in θ space • From ASTs run from BEAST models – P(θ|d) = BEAST/P(θ) ∏∫ i P(ϕ∣θ)