Statistical Challenges in Modern Astronomy IV

June 12-15, 2006
(plus associated tutorials, June 6-10)

The SCMA IV conference was held in the high-tech Berg Auditorium of the Life Sciences Building at Penn State University in State College PA on June 12-15 2006. Further conference details, registration fees and procedures, lodging, travel and visa information is available via the tabs above.

The scientific program is divided into seven topical sessions with Invited Speakers in astronomy or statistics accompanied by Commentators from the other discipline.  Brief biographies of the Speakers and Commentators are available here.

I  Cosmology

Istvan Szapudi (Hawaii)
Spatial statistics in the cosmic microwave background maps
Gary Hinshaw (NASA/GSFC)
Statistics in the WMAP experiment
Vicent Martinez (Valencia)
Cosmic structures: A challenge for astrostatistics
Adrian Baddeley (W Australia)
Analyzing spatial point pattern data
Christopher Kochanek (Ohio State)
Understanding quasar microlensing
Gary Bernstein (Penn)
The statistics of weak gravitational lensing
Michael Woodroofe (Michigan)
Shape restricted estimation in the search for Dark Matter

II  Periodic time series

John Rice (UC Berkeley)
Detecting periodicity in a Poisson process
Chris Koen (W Cape)
Periodicities in variable astronomical objects
Graham Woan (Glasgow)
Periodicity in gravitational waves

III  Recent developments in statistics

Christopher Genovese (Carnegie Mellon)
Nonparametric Inference in astrophysics and cosmology with application to Dark Energy and the CMB
Rebecca Willett (Duke)
Statistical analysis of photon-limited astronomical signals and images
Merlise Clyde (Duke)
Current challenges in Bayesian model choice
Alfred Inselberg (Tel Aviv/SDSC)
Multidimensional visualization and its applications

IV   Planetary systems

Eric Ford (UC Berkeley)
Bayesian model selection and extrasolar planet detection
William Romanishin (Oklahoma)
Statistics of the colors of Kuiper Belt Objects and Centaurs

V   Large surveys & mega-datasets

Thomas Loredo (Cornell)
Recent progress in statistical methodology for astronomical surveys
Timothy Axelrod (Arizona)
Photometric calibration: An intriguing statistical problem from the LSST
Robert Lupton (Princeton)
The characterisation, subtraction, and addition of astronomical images
Robert Hanisch (STScI/NVO)
The Virtual Observatory:  Core capabilities and support for statistical analyses in astronomy

VI  Small-N problems in physics and astronomy

Alanna Connors (Eureka)
Measuring what we "see" in Poisson images, or, Is that a bridge over the Milky Way?
Glen Cowan (Royal Holloway UL)
The small-N problem in high energy physics
Harrison Prosper (Florida State)
Bayesian methods in particle physics: From small-N to large

VII  Cross-disciplinary perspectives

Astronomy: Ofer Lahav (UC London)
Physics: Louis Lyons (Oxford)
Statistics: James Berger (Duke)

Commentators:

G. Jogesh Babu (Penn State)
Laura Cayon (Purdue)
Jayanta K. Ghosh (Purdue)
Martin Hendry (Glasgow)
Woncheol Jang (Duke)
William Jefferys (Texas/Vermont)
Ofer Lahav (UC London)
Ji Meng Loh (Columbia)
John Rice (UC Berkeley)
Jeffrey Scargle (NASA-Ames)
Jiayang Sun (Case Western Reserve)
David van Dyk (UC Irvine)
Rebecca Willett (Duke)
Michael Woodroofe (Michigan)
Zhengyuan Zhu (N Carolina)

Scientific Organizing Committee:

G. Jogesh Babu (co-chair, Penn State), James Berger (Duke), Eric Feigelson (co-chair, Penn State), Krzysztof Gorski (JPL), Thomas Loredo (Cornell), Vicent Martinez (Valencia), Larry Wasserman (Carnegie Mellon), Michael Woodroofe (Michigan)

The second annual Summer School in Statistics for Astronomers and Physicists was held at Penn State. This is a 5-day course in fundamental statistical inference designed to provide physical scientists, and graduate students, with a strong conceptual foundation in modern statistics and to develop a repertoire of well-established techniques applicable to observational astronomy and physics. Classroom instruction is interspersed with hands-on analysis of astronomical data using the public-domain R software package. The team of instructors include Professors Steven Arnold, G. J. Babu, Eric Feigelson, Murali Haran, Thomas Hettmansperger, David Hunter, Alfred Inselberg, Thomas Loredo, Donald Richards & C. R. Rao. Statistical techniques covered include:

• exploratory data analysis
• hypothesis testing and parameter estimation
  
• confidence interval estimation
• maximum likelihood methods & Bayes' Theorem
  
• non-parametric methods
• Monte Carlo methods
• Poisson processes

The 2006 Summer School was modeled on the 1st Summer School; see lecture notes for the first Summer School.