Jan 20th, 2009| 01:59 pm | Posted by hlee

Someone emailed me for globular cluster data sets I used in a proceeding paper, which was about how to determine the multi-modality (multiple populations) based on well known and new information criteria without binning the luminosity functions. I spent quite time to understand the data sets with suspicious numbers of globular cluster populations. On the other hand, obtaining globular cluster data sets was easy because of available data archives such as VizieR. Most data sets in charts/tables, I acquire those data from VizieR. In order to understand science behind those data sets, I check ADS. Well, actually it happens the other way around: check scientific background first to assess whether there is room for statistics, then search for available data sets. Continue reading ‘accessing data, easier than before but…’ »

Tags:

archive,

ascii,

catalog,

CDA,

data analysis,

data mining,

database,

Gator,

globular cluster,

inference,

massive data,

multimodality,

multiple populations,

NED,

SDSS,

statistical inference,

statistician,

streaming data,

table,

tabulated,

visieR Category:

Algorithms,

Astro,

Cross-Cultural,

Data Processing,

Jargon,

Meta,

Nuggets,

Objects |

3 Comments
Oct 27th, 2008| 11:05 am | Posted by hlee

The first step of data analysis or applications is reading the data sets into a tool of choice. Recent years, I’ve been using R (see also Learning R) for that regard but I’ve enjoyed freedoms for the same purpose from these languages and tools: BASIC, fortran77/90/95, C/C++, IDL, IRAF, AIPS, mongo/supermongo, MATLAB, Maple, Mathematica, SAS, SPSS, Gauss, ARC, Minitab, and recently Python and ciao which I just began to learn. Many of them I lost the fluency of how to use it. Quick learning tends to be flash memory. Some will need brain defragmentation and recovering time for extensive scientific work. A few I don’t like to use at all. No matter what, I’m not a computer geek. I’m not good at new gadgets, new softwares, nor welcome new and allegedly versatile computing systems. But one must be if he/she want to handle data. Until recently I believed R has such versatility in the aspect of reading in data. Yet, there is nothing without exceptions. Continue reading ‘read.table()’ »

Jan 27th, 2007| 11:47 pm | Posted by hlee

Generally, astronomical data archives are open to public. Also, astronomy has been the leading force of developing software and hardware to handle massive data, which nowadays receive spotlights from statistics. Although the astronomical data look easy to be accessed for some statistical challenges, compared to data sets of other disciplines, statistical applications on astronomical data are unlikely to be found. What is the cause of this long engagement period?

Continue reading ‘FITS to ASCII’ »