The AstroStat Slog

The Section on Bayesian Statistical Science (SBSS) of the American Statistical Association (ASA) would like to announce its 2010 student paper competition.  Winners of the competition will receive partial support for attending the 2010 Joint Statistical Meetings (JSM) in Vancouver, BC.

Eligibility

The candidate must be a member of SBSS (URL: www.amstat.org/membership/chapsection.pdf) or ISBA (International Society for Bayesian Analysis). Those candidates who have previously received travel support from SBSS are not eligible to participate. In addition, the candidate must be a full-time student (undergraduate, Masters, or Ph.D.) on or after September 1, 2009.

A manuscript, suitable for journal submission, is required for entry. The candidate must be the lead author on the paper, and hold the primary responsibility for the research and write-up.

The candidate must have separately submitted an abstract for JSM 2010 through the regular abstract submission process,  to present applied, computational, or theoretical Bayesian work. Papers should be submitted for presentation at the JSM as topic contributed or invited papers. Those papers not already a part of a session should be submitted online using the following settings:

(at URL: www.amstat.org/meetings/jsm/2010/index.cfm?fuseaction=abstracts):

* Abstract Type: Topic contributed
* Sub Type: Papers
* Sponsor: Section on Bayesian Statistical Science
* Organizer:  Alyson Wilson
* Organizer e-mail: agw -at- iastate.edu

Application Process

The deadline for application is Feb. 1 (same as the JSM 2010 abstract submission deadline). A formal application including the following materials should be emailed to Prof. Vanja Dukic (vanja -at- uchicago.edu):

a)      CV
b)      Abstract number (from the ASA JSM 2010 abstract submission)
c)      Letter from the major professor (advisor) or faculty co-author, verifying the student status of the candidate, and briefly describing the candidate’s role in the research and writing of the paper
d)      The manuscript, suitable for journal submission, in .pdf format.

Selection of Winners

Papers will be reviewed by a committee determined by the officers of the SBSS. Criteria for selection will include, but are not limited to, significance and potential impact of the research.  Decisions of the committee are final, and will be announced in the Spring before the JSM.

Prizes

Prizes will consist of a certificate to be presented at the SBSS section meeting and partial support (up to $1000) for attending the JSM.  Please note that the awards may be unable to cover the entirety of any winner’s travel, so winning candidates may need to supplement the SBSS award with other funds. To receive a monetary prize, the winner will need to provide proof of membership and submit travel receipts to the SBSS treasurer after the JSM.

Statistical Resampling Methods are rather unfamiliar among astronomers. Bootstrapping can be an exception but I felt like it’s still unrepresented. Seeing an recent review paper on cross validation from [arXiv] which describes basic notions in theoretical statistics, I couldn’t resist mentioning it here. Cross validation has been used in various statistical fields such as classification, density estimation, model selection, regression, to name a few. Continue reading ‘[ArXiv] Cross Validation’ »

Speaking of XAtlas from my previous post I tried another visualization tool called Parallel Coordinates on these Capella observations and two stars with multiple observations (AL Lac and IM Peg). As discussed in [MADS] Chernoff face, full description of the catalog is found from XAtlas website. The reason for choosing these stars is that among low mass stars, next to Capella (I showed 16), IM PEG (HD 21648, 8 times), and AR Lac (although different phases, 6 times) are most frequently observed. I was curious about which variation, within (statistical variation) and between (Capella, IM Peg, AL Lac), is dominant. How would they look like from the parametric space of High Resolution Grating Spectroscopy from Chandra? Continue reading ‘[MADS] Parallel Coordinates’ »

Approximately for a decade, there have been journals dedicated to bioinformatics. On the other hand, there is none in astronomy although astronomers have a long history of comprising a huge volume of catalogs and data archives. Prof. Bickel’s comment during his plenary lecture at the IMS-APRM particularly on sparse matrix and philosophical issues on choosing principal components led me to wonder why astronomers do not discuss astroinformatics. Continue reading ‘Astroinformatics’ »

I was reading the June 2009 IMS bulletin on my way to Korea for the 1st IMS-APRM meeting. Then, I was in half shock and in half sadness. Something unlike than the Drake equation had happened. Continue reading ‘worse than the Drake eq.’ »

Is Calculus the ultimate goal of mathematical education? Arthur Benjamin has a slightly subversive suggestion in this TED presentation.
Continue reading ‘Mt. Mathematics’ »

A Fast Thresholded Landweber Algorithm for Wavelet-Regularized Multidimensional Deconvolution
Vonesch and Unser (2008)
IEEE Trans. Image Proc. vol. 17(4), pp. 539-549

Quoting the authors, I also like to say that the recovery of the original image from the observed is an ill-posed problem. They traced the efforts of wavelet regularization in deconvolution back to a few relatively recent publications by astronomers. Therefore, I guess the topic and algorithm of this paper could drag some attentions from astronomers. Continue reading ‘Wavelet-regularized image deconvolution’ »

Even though I traced the astronomers’ casual usage of the null hypothesis probability in a fashion of reporting outputs from data analysis packages of their choice, there were still some curious cases of the null hypothesis probability that I couldn’t solve. They are quite mysterious to me. Sometimes too much creativity harms the original intention. Here are some examples. Continue reading ‘Curious Cases of the Null Hypothesis Probability’ »

How would you assign orders to multivariate data? If you have your strategy to achieve this ordering task, I’d like to ask, “is your strategy affine invariant?” meaning that shift and rotation invariant. Continue reading ‘[MADS] data depth’ »

This simple law, despite my trial of full text search, was not showing in ADS. As discussed in systematic errors, astronomers, like physicists, show their error components in two additive terms; statistical error + systematic error. To explain such decomposition and to make error analysis statistically rigorous, the law of total variance (LTV) seems indispensable. Continue reading ‘[MADS] Law of Total Variance’ »

Among billion objects in our Galaxy, outside the Earth, our Sun drags most attention from astronomers. These astronomers go by solar physicists, who enjoy the most abundant data including 400 year long sunspot counts. Their joy is not only originated from the fascinating, active, and unpredictable characteristics of the Sun but also attributed to its influence on our daily lives. Related to the latter, sometimes studying the conditions on the Sun is called space weather forecast. Continue reading ‘space weather’ »

My understandings of “robustness” from the education in statistics and from communicating with astronomers are hard to find a mutual interest. Can anyone help me to build a robust bridge to get over this abyss? Continue reading ‘Robust Statistics’ »

Almost 100 years ago, A.S. Eddington stated in his book Stellar Movements (1914) that

…in calculating the mean error of a series of observations it is preferable to use the simple mean residual irrespective of sign rather than the mean square residual

Such eminent astronomer said already least absolute deviation over chi-square, if I match simple mean residual and mean square residual to relevant methodologies, in order. Continue reading ‘a century ago’ »

I was reading Lehmann’s memoir on his friends and colleagues who influence a great deal on establishing his career. I’m happy to know that his meeting Landau, Courant, and Evans led him to be a statistician; otherwise, we, including astronomers, would have had very different textbooks and statistical thinking would have been different. On the other hand, I was surprised to know that he chose statistics over physics due to his experience from Cambridge (UK). I thought becoming a physicist is more preferred than becoming a statistician during the first half of the 20th century. At least I felt that way, probably it’s because more general science books in physics and physics related historic events were well exposed so that I became to think that physicists are more cooler than other type scientists. Continue reading ‘[Book] The Physicists’ »

http://www.tricki.org/

The wikipedia-like repository for mathematical “tricks” has now gone live. Their mission statement:

The main body of the Tricki will be a (large, if all goes according to plan) collection of articles about methods for solving mathematical problems. These will be everything from very general problem-solving tips such as, “If you can’t solve the problem, then try to invent an easier problem that sheds light on it,” to much more specific advice such as, “If you want to solve a linear differential equation, you can convert it into a polynomial equation by taking the Fourier transform.”