Jun 19th, 2008| 11:42 pm | Posted by hlee

I was questioned by two attendees, acquainted before the AAS, if I can suggest them clustering methods relevant to their projects. After all, we spent quite a time to clarify the term **clustering.** Continue reading ‘my first AAS. IV. clustering’ »

Jun 16th, 2008| 10:47 am | Posted by hlee

As Prof. Speed said, PCA is prevalent in astronomy, particularly this week. Furthermore, a paper explicitly discusses R, a popular statistics package. Continue reading ‘[ArXiv] 2nd week, June 2008’ »

Tags:

Bayesian evidence,

Binning,

broken power law,

cosmology,

K-S test,

LF,

lhs,

likelihood,

PCA,

power spectrum,

R,

SFH,

Sun,

Tully-Fisher Category:

arXiv,

MCMC |

Comment
Apr 21st, 2008| 11:56 pm | Posted by hlee

Because of the extensive works by Prof. Peebles and many (observational) cosmologists (almost always I find Prof. Peeble’s book in cosmology literature), the 2 (or 3) point correlation function is much more dominant than any other mathematical and statistical methods to understand the structure of the universe. Unusually, this week finds an astro-ph paper written by a statistics professor addressing the K-function to explore the mystery of the universe.

[astro-ph:0804.3044] J.M. Loh

**Estimating Third-Order Moments for an Absorber Catalog**

Continue reading ‘[ArXiv] Ripley’s K-function’ »

Mar 7th, 2008| 06:01 pm | Posted by hlee

Irrelevant to astrostatistics but interesting for baseball lovers.

[stat.AP:0802.4317] Jensen, Shirley, & Wyner

**Bayesball: A Bayesian Hierarchical Model for Evaluating Fielding in Major League Baseball**

With the 5th year WMAP data release, there were many WMAP related papers and among them, most statistical papers are listed. Continue reading ‘[ArXiv] 1st week, Mar. 2008’ »

Tags:

baseball,

cosmology,

MLE,

tessellation,

void,

WMAP,

XMM Category:

arXiv,

Bayesian,

Cross-Cultural,

Fitting,

Jargon,

MCMC |

Comment
Dec 14th, 2007| 05:16 pm | Posted by hlee

Jul 25th, 2007| 02:28 am | Posted by hlee

Since I began to subscribe arxiv/astro-ph abstracts, from an astrostatistical point of view, one of the most frequent topics has been **photometric redshifts**. This photometric redshift has been a popular topic as the catalog of remote photometric object observation multiplies its volume and sky survey projects in multiple bands lead to virtual observatories (VO – will discuss in the later posting). Just searching by **photometric redshifts** in google scholar and arxiv.org provides more than 2000 articles since 2000.

Continue reading ‘Photometric Redshifts’ »

Tags:

cosmology,

distance estimation,

Lutz-Kelker bias,

machine learning,

Malmquist bias,

Photometric Redshift,

spectrum,

survey,

VO Category:

Algorithms,

arXiv,

Data Processing,

Galaxies,

Stat |

Comment
Jul 16th, 2007| 01:30 pm | Posted by hlee

From arxiv/astro-ph:0707.1982v1,

**Nflation: observable predictions from the random matrix mass spectrum** by Kim and Liddle

To my knowledge, random matrix received statisticians’ interests fairly recently and SAMSI (Statistical and Applied Mathematical Sciences Institute) offered a semester long program on High Dimensional Inference and Random Matrices (tutorials and lecture notes can be found) during Fall 2006 . However, my knowledge is very limited to make a comment or critic on Kim and Liddle’s paper. Clearly, nonetheless, this paper is not about random matrix theory but about its straightforward application to the cosmological model viability.

Continue reading ‘[ArXiv] Random Matrix, July 13, 2007’ »

Jun 18th, 2007| 03:06 pm | Posted by hlee

From arxiv/astro-ph:0706.1988,

Lectures on Astronomy, Astrophysics, and Cosmology looks helpful to statisticians who like to know astronomy, astrophysics, and cosmology. The lecture note starts from introducing fundamentals of astronomy, UNITS!!!, and its history. It also explains astronomical measures such as distances and their units, luminosity, and temperature; HR diagram (astronomers’ summary diagram); stellar evolution; and relevant topics in cosmology. At least, a third of the article will be useful to grasp a rough idea of astronomy as a scientific subject beyond colorful pictures. Statisticians who are keen to cosmology are recommended to read beyond.

This is not a high energy lecture note; therefore, statisticians interested in high energy are encouraged to visit Astro Jargon for Statisticians and CHASC.