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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Advanced Statistical Methods for Astrophysical Probes of Cosmology

Advanced Statistical Methods for Astrophysical Probes of Cosmology

March, Marisa Cristina

Paperback

Series: Springer Theses

Astronomy & SpaceProbability & Statistics

ISBN10: 3642444547
ISBN13: 9783642444548
Publisher: Springer
Published: Feb 8 2015
Pages: 180
Weight: 0.63
Height: 0.42 Width: 6.14 Depth: 9.21
Language: English
This thesis explores advanced Bayesian statistical methods for extracting key information for cosmological model selection, parameter inference and forecasting from astrophysical observations. Bayesian model selection provides a measure of how good models in a set are relative to each other - but what if the best model is missing and not included in the set? Bayesian Doubt is an approach which addresses this problem and seeks to deliver an absolute rather than a relative measure of how good a model is. Supernovae type Ia were the first astrophysical observations to indicate the late time acceleration of the Universe - this work presents a detailed Bayesian Hierarchical Model to infer the cosmological parameters (in particular dark energy) from observations of these supernovae type Ia.

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