Presentations 

Workshop 20 Sep 2017 10am4pm EDT Phillips Auditorium at CfA 
 AstroStat Day
 10:00am  12:10pm : Siemiginowska, Vikhlinin, Finkbeiner, Portillo, Daylan, Speagle, B. Johnson
 12:30pm  1:30pm : Reeves, Winter
(SolarStat, in conjunction with HEAD Lunch Talks)
 2:00pm  4:00pm : Grindlay, M. Johnson, Blackburn, Bouman, Avelino, Zucker
 4:00pm  5:00pm : Discussion


Josh Speagle (CfA) 26 Sep 2017 1:07pm EDT Pratt (PerkinG, CfA) 
 Dynamic Nested Sampling
 Nested Sampling is a relatively new method for estimating the Bayesian evidence (with the posterior estimated as a byproduct) that integrates over the posterior by sampling in nested "shells" of constant likelihood. Its ability to sample from complex, multimodal distributions in a flexible yet efficient way combined with several available sampling packages has contributed to its growing popularity in (astro)physics. In this talk I will outline the basic motivation and theory behind Nested Sampling, derive various statistical properties associated with the method, and discuss how it is applied in practice. I will then talk about how the overall framework can be extended in Dynamic Nested Sampling to accommodate adding samples "dynamically" during the course of a run. These samples can be allocated to maximize arbitrary objective functions, allowing Dynamic Nested Sampling to function as a posteriororiented sampling method such as MCMC but with the added benefit of welldefined stopping criteria. I will end by applying Dynamic Nested Sampling to a variety of synthetic and realworld problems using an opensource Python package I've been developing (dynesty).
 Presentation slides [.pdf]
 See also: MultiNest ; PolyChord [url


Gabriel Collin (MIT) 21 Nov 2017 1:07pm EST Pratt (PerkinG, CfA) 
 Searching for the origin of astrophysical neutrinos using a nonPoissonian statistical method
 Abstract: The IceCube neutrino observatory was designed to detect astrophysical neutrinos, which originate from outside of our solar system. IceCube has detected candidate astrophysical events, and measured a diffuse flux, but the source of these neutrinos so far remains unknown. Current approaches look for "hot spots" of neutrino events in the sky. It is also possible to describe a population of sources in terms of the number of observed events, forming a nonPoissonian statistical distribution. This distribution was used to show that the excess of gamma rays measured by FermiLAT around the galactic center was likely due to point sources rather than decaying dark matter. In this talk, I will present the application of this statistical method to the search for point sources in IceCube.


Katy McKeough & Shihao Yang (Harvard) 28 Nov 2017 1:07pm EST SciCen 706 
 LIRA+Ising


Katy McKeough, Luis Campos, Shihao Yang (Harvard) 12 Dec 2017 12:37pm EST CfA Library 
 Ask A Statistician
 An oppportunity for astronomers at the CfA to ask statistics questions of statisticians.
From the mundane to the philosophical, bring your statistics problems to be discussed by the panel.
Fill out the online form to ask the question or state the problem.





