Archive for the ‘Astro’ Category.


The year 2009 is the Darwin bicentennial and the sesquicentennial of the publication of the Origin of Species, but, um, even more importantly, it is the International Year of Astronomy, celebrating 400 orbits since Galileo started to look through a telescope.


We have seen the word “bipartisan” often during the election and during the on-going recession period. Sometimes, I think that the bipartisanship is not driven by politicians but it’s driven by media, commentator, and interpreters. Continue reading ‘Bipartisanship’ »

Borel Cantelli Lemma for the Gaussian World

Almost two year long scrutinizing some publications by astronomers gave me enough impression that astronomers live in the Gaussian world. You are likely to object this statement by saying that astronomers know and use Poisson, binomial, Pareto (power laws), Weibull, exponential, Laplace (Cauchy), Gamma, and some other distributions.[1] This is true. I witness that these distributions are referred in many publications; however, when it comes to obtaining “BEST FIT estimates for the parameters of interest” and “their ERROR (BARS)”, suddenly everything goes back to the Gaussian world.[2]

Borel Cantelli Lemma (from Planet Math): because of mathematical symbols, a link was made but any probability books have the lemma with proofs and descriptions.

Continue reading ‘Borel Cantelli Lemma for the Gaussian World’ »

  1. It is a bit disappointing fact that not many mention the t distribution, even though less than 30 observations are available.[]
  2. To stay off this Gaussian world, some astronomers rely on Bayesian statistics and explicitly say that it is the only escape, which is sometimes true and sometimes not – I personally weigh more that Bayesians are not always more robust than frequentist methods as opposed to astronomers’ discussion about robust methods.[]

[SPS] Testing Completeness

There will be a special session at the 213th AAS meeting on meaning from surveys and population studies (SPS). Until then, it might be useful to pull out some interesting and relevant papers and questions/challenges as a preliminary to the meeting. I will not list astronomical catalogs and surveys only, which are literally countless these days but will bring out some if they change the way how science is performed with a description of the catalog (the best example would be SDSS, Sloan Digital Sky Survey, to my knowledge). Continue reading ‘[SPS] Testing Completeness’ »

It bothers me.

The full description is given about “bayes” under sherpa/ciao[1]. Some sentences kept bothering me and here’s my account for the reason given outside of quotes. Continue reading ‘It bothers me.’ »

  1. Note that the current sherpa is beta under ciao 4.0 not under ciao 3.4 and a description about “bayes” from the most recent sherpa is not available yet, which means this post needs updates one new release is available[]

after “Thanks to Henrietta Leavitt”

Personally, it was a highly anticipated symposium at CfA because I was fascinated about the female computers’ (or astronomers’) contributions that occurred here about a century ago even though at that time women were not considered as scientists but mere assistants for tedious jobs. Continue reading ‘after “Thanks to Henrietta Leavitt”’ »

“Thanks to Henrietta Leavitt”


The CfA is celebrating the 100th anniversary of the discovery of the Cepheid period-luminosity relation on Nov 6, 2008. See for details.

[Update 10/03] For a nice introduction to the story of Henrietta Swan Leavitt, listen to this Perimeter Institute talk by George Johnson:

[Update 11/06] The full program is now available. The symposium begins at Noon today.

Astroart Survey

Astronomy is known for its pretty pictures, but as Joe the Astronomer would say, those pretty pictures don’t make themselves. A lot of thought goes into maximizing scientific content while conveying just the right information, all discernible at a single glance. So the hardworkin folks at Chandra want your help in figuring out what works and how well, and they have set up a survey at Take the survey, it is both interesting and challenging!


RMF. It is a wørd to strike terror even into the hearts of the intrepid. It refers to the spread in the measured energy of an incoming photon, and even astronomers often stumble over what it is and what it contains. It essentially sets down the measurement error for registering the energy of a photon in the given instrument.

Thankfully, its usage is robustly built into analysis software such as Sherpa or XSPEC and most people don’t have to deal with the nitty gritty on a daily basis. But given the profusion of statistical software being written for astronomers, it is perhaps useful to go over what it means. Continue reading ‘Redistribution’ »

missing data

The notions of missing data are overall different between two communities. I tend to think missing data carry as good amount of information as observed data. Astronomers…I’m not sure how they think but my impression so far is that a missing value in one attribute/variable from a object/observation/informant, all other attributes related to that object become useless because that object is not considered in scientific data analysis or model evaluation process. For example, it is hard to find any discussion about imputation in astronomical publication or statistical justification of missing data with respect to inference strategies. On the contrary, they talk about incompleteness within different variables. Putting this vague argument with a concrete example, consider a catalog of multiple magnitudes. To draw a color magnitude diagram, one needs both color and magnitude. If one attribute is missing, that star will not appear in the color magnitude diagram and any inference methods from that diagram will not include that star. Nonetheless, one will trying to understand how different proportions of stars are observed according to different colors and magnitudes. Continue reading ‘missing data’ »


Contact has been re-established with XMM-Newton. Continue reading ‘Whew’ »

“planetariums and other foolishness”

Last month, Senator McCain (R-AZ) wildly dissed on Chicago’s Adler Planetarium, characterizing a funding request on its behalf as “planetariums and other foolishness.” Continue reading ‘“planetariums and other foolishness”’ »

Killer App

The iPhone is an amazing device. I have heard that some people use it as a phone, too, but it really is an extraordinary portable computer. It is faster and more powerful than the Sparcstations I used as a grad student, and will fit into your pocket. And most importantly, you can fit an entire planetarium on it.

There are many good planetarium programs that you can access on laptops, but it is really not that much fun to lug them around on camping trips or even out on to the roof at night. But now, thanks to the iPhone (and the iPod Touch) there has been a great leap forward. Continue reading ‘Killer App’ »

The Big Picture

Our hometown rag (the Boston Globe) runs an occasional series of photo collections that highlight news stories called The Big Picture. This week, they take a look at the Sun:

The pictures come from space and ground observatories, from SoHO, TRACE, Hinode, STEREO, etc. Goes without saying, the images are stunning, and some are even animated. The real kicker is that images such as these are being acquired by the hundreds, every hour upon the hour, 24/7/365.25 . It is like sipping from a firehose. Nobody can sit there and look at them all, so who knows what we are missing out on. Can statistics help? Can we automate a statistically robust “interestingness” criterion to filter the data stream that humans can then follow up on?

A Quote on Model

In order to understand a learning procedure statistically it is necessary to identify two important aspects: its structural model and its error model. The former is most important since it determines the function space of the approximator, thereby characterizing the class of functions or hypothesis that can be accurately approximated with it. The error model specifies the distribution of random departures of sampled data from the structural model.

Continue reading ‘A Quote on Model’ »