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Statistics 310hfr 2004-2005
Last Updated: 2005jul26

Astro-Statistics Seminar

Statistics 310hfr, Fall/Winter 2004-2005

Harvard University

www.courses.fas.harvard.edu/~stat310/

Presentations at the Astro-Statistics Seminar, Stat 310, taught by Xiao-Li Meng (Harvard). Note: List still incomplete.
Aneta Siemiginowska, CfA
21 Sep 2004
Astronomy in the Age of Space: An Overview [.pdf]
This is a broad overview of astronomy as an introduction to Astrostatistics. We describe research methods and techniques, as well as questions posed by some recent observations. We concentrate on problems related to high energy astrophysics and consider the data obtained by modern X-ray space telescopes such as Chandra X-ray Observatory and XMM-Newton. In this first lecture we define basic astronomical terms and present different type of data used by astrophysicists. We also describe statistical methods applied in the standard data analysis process. We show examples of the data analysis and physical interpretation of the results.
Alanna Connors, Eureka Scientific
05 Oct 2004
Astronomy Instruments from the Quantum Age: Do New Instruments, or New Ideas, Drive New Science? [.ppt]
The atomic and nuclear age of the past century allowed astronomers (and others) to peer into the "invisible world" of high- and low- energy radiation, from radio waves to gamma-rays, to see and understand the underlying quantum- and relativistic processes. How did the inference techniques change and grow with the new sciences? In this presentation, we go over the growth (and stagnation, sometimes!) of statistics in modern astrophysics; from the eye-and-hand techniques to more sophisticated imaging, energy-spectra, and timing methods. We will have some of the early instrumentation, and stories from that time, on hand -- as well as models of new twenty-first century instruments.
Vinay Kashyap, CfA
09 Nov 2004
Red atoms and Blue atoms: Astrophysical Inference using Spectral Lines [.ppt]
The foundations of astrophysics are rooted in photon spectra, and spectral energy distributions are generally our sole source of information on the composition and environment of extrasolar objects. We will introduce concepts such as atomic lines, line and continuum emission, ionization balance, and emission measure distributions, with emphasis on how they are used to understand the coronae of solar like stars.
Andreas Zezas, CfA
30 Nov 2004
X-ray observations of neutron stars and black holes in nearby galaxies [.pdf]
Jonathan Devor, CfA
22 Feb 2005
On detemining spectral types from light curves
Jeremy Drake, CfA
22 Feb 2005
On Systematic Errors and Calibration
Eric Kolaczyk, BU
08 Mar 2005
Multiscale GLMs w/ Appl to Poisson Time Series [.pdf]
I will describe an extension of the standard wavelet-based estimation framework to the class of generalized linear models, based on the use of recursive partitioning and piecewise polynomials. Estimates produced in this setting yield information on both scale and extent of local structure in an underlying time series. They are accompanied by both efficient algorithms and near-optimal theoretical properties. I will illustrate the use of these models in the context of estimating flux underlying gamma-ray burst signals. Numerous extensions are possible.
Rima Izem, HU
22 Mar 2005
Principal Components Analysis
Hosung Kang, HU
05 Apr 2005
Distribution of the Temperature of Stellar Corona (DEM) [.pdf]
I will continue to talk about the on-going project for estimating the distribution of the temperature of stellar corona also known as the differential emission measure (DEM).
I will focus on hierarchical missing data structuring and handling the emissivity matrices in terms of efficient data augmentation.
Correcting the wavelength errors at ATOMDB will be discussed. I will provide the model diagnostics related to the error correction by using posterior predictive distribution.
Yaming Yu, HU/UC (Irvine)
19 Apr 2005
Statistical Modeling of Sunspot Cycles [.pdf]
David van Dyk, UC (Irvine)
17 May 2005
High Energy Astrophysics: What do Statistical Methods Have to Offer? [.pdf]

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