Pre-conference Tutorials (June 11-12, 2011)

June 11, 2011 (Saturday)

9 am -10 am: Registration and continental breakfast.
Lectures start at 10 am

June 12, 2011 (Sunday)

Lectures start at 10 am

Bayesian computation: MCMC and all that

7 Life Sciences Building         Supernova redshifts and distance moduli data (SN.dat).
SN_project.pdf     SN_MCMC_Original.R     Alan Heavens Lectures
Bayesian approaches to astrophysical modeling of astronomical data have emerged as a major tool. However, the computational procedures can be complex with many options. This tutorial reviews these methods with emphasis on Monte Carlo Markov chain techniques.
Tom Loredo (Cornell), David van Dyk (UC Irvine), Alan Heavens (Edinburgh)
 

Data mining

4 Life Sciences Building         Booklet
Clustering, classification, regression and rule learning are important tools for interpreting astronomical megadatasets that are too large to be directly examined. Techniques for these tasks will be presented with application to modern datasets, including those compiled from the heterogeneous Virtual Observatory.
David Banks (Duke), Kirk Borne (GMU)
 

R for astronomers

6 Life Sciences Building         Booklet
R, the largest public-domain statistical programming software system, is a high-level analysis and graphical language resembling IDL. Base R provide a broad range of standard statistical funcationalities,and is accompanied by a huge and growing collection of add-on specialized packages (CRAN). R and CRAN will be introduced in hands-on tutorials using contemporary astronomical datasets.
Eric Feigelson (Penn State), David Hunter (Penn State)