[ArXiv] 2nd week, Dec. 2007
No shortage in papers~
[ArXiv] Spatial Correlation in the Scan Statistic
Accounting for Spatial Correlation in the Scan Statistic by Loh &Zhu [stat.AP:0712.1458] provides a picture that helps us to understand excessive false alarms in source detection when the image data set is based on the Poisson point process. Without any experience in source detection analysis, empirically I cannot state the detection statistics nor the p-values of detection methods. However, with acknowledging the over-dispersed Poisson count data and the unknown spatial correlation prior to detecting analysis, we could guess that the false discovery of sources occurs more often than what we expect.
[ArXiv] The Importance of Being First: Position Dependent Citation Rates on arXiv:astro-ph
The full article is found from [arXiv/astro-ph:0712.1037]. According to J. P. Dietrich, the positional citation effect (PCE) is significant so that preprints appeared at the top of daily lists tend to be more cited than other preprints. Although the study is not statistically rigorous to confirm that up to 6th article on the list is more likely cited, the number are drastically large enough to make people believe the author’s hypothesis.
[ArXiv] 1st week, Dec. 2007
There’s only one day in the first week of December with no preprint appearance. Dubbing the week of Dec. 2nd as the first week is hoped to be accepted.
Too many syllables?
Stumbled across this “blog readability test“, and
[ArXiv] 5th week, Nov. 2007
Astronomers are hard working people, day and night, weekend and weekdays, 24/7, etc. My vacation delayed this week’s posting, not astronomers nor statisticians.
[ArXiv] 4th week, Nov. 2007
A piece of thought during my stay in Korea: As not many statisticians are interested in modern astronomy while they look for data driven problems, not many astronomers are learning up to date statistics while they borrow statistics in their data analysis. The frequency is quite low in astronomers citing statistical journals as little as statisticians introducing astronomical data driven problems. I wonder how other fields lowered such barriers decades ago.
No matter what, there are preprints from this week that may help to shrink the chasm.
[ArXiv] 3rd Week, Nov. 2007
Greetings from Korea. I found that the menu on the right was almost invisible from my mother’s computer. The look seems OS and browser dependent. If you find any problems of viewing the slog, please notify me. Otherwise, please find a paper or two that drag your attention.
[ArXiv] 2nd week, Nov. 2007
There should be at least one paper that drags your attention. Various statistics topics appeared in astro-ph this week.
The Digital Universe
Another one in the CXC/CfA Visualizing Astronomy series: “The Digital Universe: Cosmic Cartography and Data Visualization”, by Brian Abbott of Hayden Planetarium & Department of Astrophysics, next Tuesday, Nov 13, at 2pm in Phillips.
[ArXiv] Post Model Selection, Nov. 7, 2007
Today’s arxiv-stat email included papers by Poetscher and Leeb, who have been working on post model selection inference. Sometimes model selection is misled as a part of statistical inference. Simply, model selection can be considered as a step prior to inference. How you know your data are from chi-square distribution, or gamma distribution? (this is a model selection problem with nested models.) Should I estimate the degree of freedom, k from Chi-sq or α and β from gamma to know mean and error? Will the errors of the mean be same from both distributions?
An example of chi2 bias in fitting the X-ray spectra.
The chi2 bias can affect the results of the X-ray spectral fitting and it
can be demonstrated in a simple way. The described simulations can be done
in Sherpa or XSPEC, the two software packages that allow for simulating the X-ray
spectra using a function called “fakeit”.
Here I assume an absorbed power law model with the sets of 3 parameters
(absorption column, photon index, and normalization) to simulate Chandra X-ray
spectrum given the instrument calibration files (RMF/ARF) and the Poisson noise.
The resulting simulated X-ray spectrum contains the model predicted counts with
the Poisson noise. This spectrum is then fit with the absorbed power law model to get
the best fit parameter values for NH, photon index and normalization.
I simulate 1000 spectra and fit each of them using different statistics: chi2 data variance,
chi2 model variance and Cash/C-statistics.
The next step is to plot the simulated distributions of the parameters and compare them
to the assumed values for the simulations. The figure shows the distribution of the photon
index parameter obtain from the fit of the spectra generated for the assumed simulated value
of 1.267. The chi2 bias is evident in this analysis, while the
CSTAT and Cash statistics based on the likelihood behave well. chi2 model variance
underestimates the simulated value, chi2 data variance overestimates this parameter.
[ArXiv] 1st week, Nov. 2007
To be exact, the title of this posting should contain 5th week, Oct, which seems to be the week of EGRET. In addition to astro-ph papers, although they are not directly related to astrostatistics, I include a few statistics papers which may be profitable for astronomical data analysis.
[ArXiv] An unbiased estimator, May 29, 2007
From arxiv/astro-ph:0705.4199v1
In search of an unbiased temperature estimator for statistically poor X-ray spectra
A. Leccardi and S. Molendi
There was a delay of writing about this paper, which by accident was lying under the pile of papers irrelevant to astrostatistics. (It has been quite overwhelming to track papers with various statistical applications and papers with rooms left for statistical improvements from arxiv:astro-ph). Although there is a posting about this paper (see Vinay’s posting), I’d like to give a shot. I was very excited because I haven’t seen any astronomical papers discussing unbiased estimators solely.
[ArXiv] 4th week, Oct. 2007
I hope there are a paper or two drags your attentions and stimulates your thoughts in astrostatistics from arXiv.