Author Archive

Clay Public Lecture: Technology-driven Statistics

I found the following from Harvard Statistics department website.

Clay Public Lecture
Technology-driven Statistics
Terry Speed, UC Berkeley and WEHI in Melbourne, Australia
Tuesday, October 30, 2007, at 7:00 PM
Harvard University Sceince Center — Hall B

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[ArXiv] 3rd week, Oct. 2007

Quite interesting papers were up at arXiv, including a theoretical statistics paper that no astronomer manages to miss. To find the paper and others, please click
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[ArXiv] 2nd week, Oct. 2007

Frankly, there was no astrostatistically interesting paper from astro-ph this week but profitable papers from the statistics side were posted. For the list, click Continue reading ‘[ArXiv] 2nd week, Oct. 2007’ »

[ArXiv] 1st week, Oct. 2007

This week, instead of only filtering AstroStatistics related papers from arxiv, I chose additional arxiv/astro-ph papers related to CHASC folks’ astrophysical projects. Some of papers you see from this week do not have sophisticated statistical analysis but contain data from specific satellites and possibly relevant information related to CHASC projects. Due to the CHACS’ long history (we are celebrating the 10th birthday this year) and my being a newbie to CHASC, I may not pick up all papers related to the projects of current, former, and future CHASC members and dedicated slog readers. For creating a satisfying posting every week, your inputs are welcome to improve my adaptive filter. For the list of this week, click the following.
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Implement Bayesian inference using PHP

Not knowing much about java and java applets in a software development and its web/internet publicizing, I cannot comment what is more efficient. Nevertheless, I thought that PHP would do the similar job in a simpler fashion and the followings may provide some ideas and solutions for publicizing statistical methods through websites based on Bayesian Inference.
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[ArXiv] 4th week, Sept. 2007

A few papers from astro-ph may drag statisticians’ attention and a statistical paper may be helpful for astronomers, keen on confidence intervals utilizing prior information.
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P Values: What They Are and How to Use Them

After observing the recent discussion among CHASC, the following paper
P Values: What They Are and How to Use Them by Luc Demortier emerged from my mind.
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[ArXiv] 3rd week, Sept. 2007

In addition to Short Timescale Coronal Variability in Capella [astro-ph:0709.3093], there were a few statistically interesting preprints came during the 3rd week of Sept. Continue reading ‘[ArXiv] 3rd week, Sept. 2007’ »

VOConvert (ConVOT)

VOConvert or ConVOT is a small java script which does file format conversion from fits to ascii or the other way around. These tools might be useful for statisticians who want to convert astronomers’ data format called fits into ascii quickly for a statistical analysis. Additionally, VOConvert creates an interim output for VOStat, designed for statistical data analysis from Virtual Observatory. The softwares and the list of Virtual Observatories around the world can be found at Virtual Observatory India. Please, check a link in VOstat (http://hea-www.harvard.edu/AstroStat/slog/2007/vostat) for more information about VOstat.

PHYSTAT-LHC 2007

The idea that some useful materials related to the Chandra calibration problem, which CHASC is putting an effort to, could be found from PHYSTAT conferences came along. Owing to the recent advanced technologies adopted by physicists (I haven’t seen any statistical conference offers what I obtained from PHYSTAT-LHC 2007), I had a chance to go through some video files from PHYSTAT-LHC 2007. The files are the recorded lectures and lecture notes. They are available from PHYSTAT-LHC 2007 Program.
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[ArXiv] 2nd week, Sept. 2007

How to subscribe to the arXiv email list service

Over the years, I noticed the exponential increase of statistical applications from astronomical papers. Keeping the track of them and writing summaries based on daily arXiv updates for the slog over the past few months has become a quite overwhelming task for a single person. Therefore, instead of offering fish, I decide to offer how to catch fish.
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[ArXiv] SVM and galaxy morphological classification, Sept. 10, 2007

From arxiv/astro-ph:0709.1359,
A robust morphological classification of high-redshift galaxies using support vector machines on seeing limited images. I Method description by M. Huertas-Company et al.

Machine learning and statistical learning become more and more popular in astronomy. Artificial Neural Network (ANN) and Support Vector Machine (SVM) are hardly missed when classifying on massive survey data is the objective. The authors provide a gentle tutorial on SVM for galactic morphological classification. Their source code GALSVM is linked for the interested readers.
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[ArXiv] Bimodal Color Distribution in GCS, Sept. 7, 2007

From arxiv/astro-ph:0709.1073v1
On the Metallicity-Color Relations and Bimodal Color Distributions in Extragalactic Globular Cluster Systems by M. Cantiello and J. P. Blakeslee

Many observations on globular cluster systems (GCS) show bimodal distributions in color and metallicity space. The authors discussed the complication of non-linear metalicity and color relations and presented their careful study to suggest the optimal color(s) for revealing the presence of real bimodal GC metallicity distributions. Based on their simulation study, (V-H) and (V-K) are confirmed to be good colors for revealing unbiased bimodal metallicity distributions in GCS.
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[ArXiv] Recent bayesian studies from astro-ph

In the past month, I’ve noticed relatively frequent paper appearance in arxiv/astro-ph whose title includes Bayesian or Markov Chain Monte Carlo (MCMC). Those papers are:

  • [astro-ph:0709.1058v1] Joint Bayesian Component Separation and CMB Power Spectrum Estimation by H.K.Eriksen et. al.
  • [astro-ph:0709.1104v1] Monolithic or hierarchical star formation? A new statistical analysis by M. Kampakoglou, R. Trotta, and J. Silk
  • [astro-ph:0411573v2] A Bayesian analysis of the primordial power spectrum by M.Bridges, A.N.Lasenby, M.P.Hobson
  • [astro-ph:0709.0596v1] Bayesian inversion of Stokes profiles by A. A. Ramos, M.J.M. Gonzales, and J.A. Rubino-Martin
  • [astro-ph:0709.0711v1] Bayesian posterior classification of planetary nebulae according to the Peimbert types by C. Quireza, H.J.Rocha-Pinto, and W.J. Maciel
  • [astro-ph:0708.2340v1] Bayesian Galaxy Shape Measurement for Weak Lensing Surveys -I. Methodology and a Fast Fitting Algorithm by L. Miller et. al.
  • [astro-ph:0708.1871v1] Dark energy and cosmic curvature: Monte-Carlo Markov Chain approach by Y. Gong et. al.

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