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Abstract Details
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Activity Number:
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387
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Type:
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Invited
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Date/Time:
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Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #300334 |
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Title:
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Statistical Inference for Astronomical Populations from Truncated Data Sets
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Author(s):
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Brandon Kelly*+
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Companies:
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Harvard-Smithsonian Center for Astrophysics
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Address:
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60 Garden St., MS-06, Cambridge, MA, 02138, US
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Keywords:
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Bayesian Statistics ;
Astrophysics ;
Measurement Error ;
Truncation
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Abstract:
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Understanding demographics of astronomical populations and their evolution is often one of the primary goals of large astronomical surveys. However, this is not always a straightforward task in that the physical quantities, such as mass, that one is interested in are not directly measurable, but rather they are derived from measurable quantities, such as brightness, with uncertainty. Moreover, the situation is complicated by data truncation caused by brightness limits of telescopes. This complicates statistical inference on these populations, making it difficult to recover their evolution. In this talk I will discuss a Bayesian approach to this problem, as well as recent application of this approach to astronomical surveys. I will conclude by outlining areas for further improvement.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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