The AstroStat Slog » bimodality http://hea-www.harvard.edu/AstroStat/slog Weaving together Astronomy+Statistics+Computer Science+Engineering+Intrumentation, far beyond the growing borders Fri, 09 Sep 2011 17:05:33 +0000 en-US hourly 1 http://wordpress.org/?v=3.4 my first AAS. V. measurement error and EM http://hea-www.harvard.edu/AstroStat/slog/2008/first-aas-measurement-error-and-em/ http://hea-www.harvard.edu/AstroStat/slog/2008/first-aas-measurement-error-and-em/#comments Fri, 20 Jun 2008 03:46:05 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/?p=336 While discussing different view points on the term, clustering, one of the conversers led me to his colleague’s poster. This poster (I don’t remember its title and abstract) was my favorite from all posters in the meeting.

He rewrote the EM algorithm to include measurement errors in redshifts. Indexed parameters associated with different redshifts and corresponding standard deviations (measurement errors, treated as nuisance parameters) were included in the likelihood function that corrected bias and manifested bimodality in the LFs clearly at the different evolutionary stages.

I encouraged him to talk statisticians to characterize and to generalize his measurement error included likelihoods, and to optimize his EM algorithm. Because of approximations in algebra and the many parameters from measurement errors from redshifts, some assumptions and constraints were imposed intensively and I thought a collaboration with statisticians suits to get around constraints and to generalize his measurement error included likelihood.

]]> http://hea-www.harvard.edu/AstroStat/slog/2008/first-aas-measurement-error-and-em/feed/ 1 [ArXiv] 2nd week, May 2008 http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-2nd-week-may-2008/ http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-2nd-week-may-2008/#comments Mon, 19 May 2008 14:42:56 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/?p=306 There’s no particular opening remark this week. Only I have profound curiosity about jackknife tests in [astro-ph:0805.1994]. Including this paper, a few deserve separate discussions from a statistical point of view that shall be posted.

  • [astro-ph:0805.1290]R. Barnard, L. Shaw Greening, U. Kolb
    A multi-coloured survey of NGC 253 with XMM-Newton: testing the methods used for creating luminosity functions from low-count data

  • [astro-ph:0805.1469] Philip J. Marshall et al.
    Automated detection of galaxy-scale gravitational lenses in high resolution imaging data

  • [astro-ph:0805.1470] E. P. Kontar, E. Dickson, J. Kasparova
    Low-energy cutoffs and in electron spectra of solar flares: statistical survey (It is not statistically rigorous but the topic can be connected to dip tests or gap tests in statistics)

  • [astro-ph:0805.1936] J. Yee & B. Gaudi
    Characterizing Long-Period Transiting Planets Observed by Kepler (discusses uncertainty in light curves and Fisher matrix)

  • [astro-ph:0805.1994] the QUad collaboration: C. Pryke et al.
    Second and third season QUaD CMB temperature and polarization power spectra (What is jackknife tests? A brief scan of the paper does not register with my understanding of jackknifing. It looks more close to cross validation. Another slog topic shall come: bootstrap, cross validation, jackknife, and resampling.)

  • [astro-ph:0805.2121] N. Cole et al.
    Maximum Likelihood Fitting of Tidal Streams With Application to the Sagittarius Dwarf Tidal Tails

  • [astro-ph:0805.2155] J Yoo & M Zaldarriaga
    Improved estimation of cluster mass profiles from the cosmic microwave background

  • [astro-ph:0805.2207] A.Vikhlinin et al.
    Chandra Cluster Cosmology Project II: Samples and X-ray Data Reduction (it mentions calibration uncertainty and background, can it be a reference to stacking, coadding, source detection, etc?)

  • [astro-ph:0805.2325] J.M. Loh
    A valid and fast spatial bootstrap for correlation functions

  • [astro-ph:0805.2326] T. Wickramasinghe, M. Struble, J. Nieusma
    Observed Bimodality of the Einstein Crossing Times of Galactic Microlensing Events
]]> http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-2nd-week-may-2008/feed/ 0 [ArXiv] 4th week, Feb. 2008 http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-4th-week-feb-2008/ http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-4th-week-feb-2008/#comments Mon, 03 Mar 2008 17:39:07 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-4th-week-feb-2008/ In this posting, I added lecture notes on cosmic microwave background (CMB) and Gravitas DVD (animation, I believe). There is another paper I must include but I decide to write a short review separately.

  • [astro-ph:0802.3411] N.Seto
       Detecting Planets around Compact Binaries with Gravitational Wave Detectors in Space

  • [astro-ph:0802.3599] Jones & van de Weygaert
       Cosmic Order out of Primordial Chaos: a tribute to Nikos Voglis

  • [astro-ph:0802.3764] J. Southworth
       Homogeneous studies of transiting extrasolar planets. I. Light curve analyses

  • [astro-ph:0802.3914] A. M. Wolfe et.al.
        Bimodality in Damped Lyman alpha Systems (Kolmogorov-Smirnoff test)

  • [astro-ph:0802.3931] M.S. Wheatland
       The Energetics of a Flaring Solar Active Region, and Observed Flare Statistics

A paper linked with an animation: [astro-ph:0802.3664] Dubinski and Farah
    GRAVITAS: Portraits of a Universe in Motion (I wanted to but I couldn’t watch.)
Lecture notes on CMB: [astro-ph:0802.3688] Wayne Hu
    Lecture Notes on CMB Theory: From Nucleosynthesis to Recombination

]]> http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-4th-week-feb-2008/feed/ 0 [ArXiv] 5th week, Jan. 2008 http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-5th-week-jan-2008/ http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-5th-week-jan-2008/#comments Fri, 01 Feb 2008 18:01:03 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-5th-week-jan-2008/ Some statistics papers were listed at the top, of which topics would interest some slog subscribers.

From statistics arxiv:

  • [stat.CO:0801.3387] Contemplating Evidence: properties, extensions of, and alternatives to Nested Sampling N. Chopin &C. Robert
  • [math.ST:0801.4329] Estimators of Long-Memory: Fourier versus Wavelets G. Fay et.al. (not comprehensible but the title is more than interesting)

From astro-ph:

  • [astro-ph:0801.4041] Quantifying parameter errors due to the peculiar velocities of type Ia supernovae R. Ali Vanderveld
  • [astro-ph:0801.4233] Effects of the interaction between dark energy and dark matter on cosmological parameters J. He & B. Wang
  • [astro-ph:0801.4889] Temporal variability and statistics of the Strehl ratio in adaptive-optics images S. Gladysz
  • [astro-ph:0801.4751] Low-Luminosity Gamma-Ray Bursts as a Distinct GRB Population:A Monte Carlo Analysis F Virgili, E Liang, &B Zhang
  • [astro-ph:0801.4759] Optical afterglow luminosities in the Swift epoch: confirming clustering and bimodality M. Nardini, G. Ghisellini & G. Ghirlanda

(The last two papers mentioned Kolmogorov-Smirnov test and probability)

]]> http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-5th-week-jan-2008/feed/ 0 The last [ArXiv] of 2007 http://hea-www.harvard.edu/AstroStat/slog/2007/the-last-arxiv-of-2007/ http://hea-www.harvard.edu/AstroStat/slog/2007/the-last-arxiv-of-2007/#comments Mon, 31 Dec 2007 18:06:16 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/2007/the-last-arxiv-of-2007/ This will be the last [ArXiv] of this year (for some of you, the previous year).

  • [astro-ph:0712.3797] Variable stars across the observational HR diagram L. Eyer & N. Mowlavi
  • [astro-ph:0712.3800] Merger history trees of dark matter haloes J. Moreno & R. K. Sheth
  • [astro-ph:0712.3833] Redshift periodicity in quasar number counts from Sloan Digital Sky Survey J. G. Hartnett
  • [astro-ph:0712.4023] On the Origin of Bimodal Horizontal-Branches in Massive Globular Clusters: The Case of NGC 6388 and NGC 6441 S. Yoon et.al.
  • [astro-ph:0712.4140] Bayesian Image Reconstruction Based on Voronoi Diagrams G. F. Cabrera, S.Casassus & N. Hitschfeld
  • [stat.TH:0712.4250] Goodness of fit test for weighted histograms N. D. Gagunashvili
  • [astro-ph:0712.2539] Nonergodicity and central limit behavior for systems with long-range interactions A. Pluchino & A. Rapisarda
]]> http://hea-www.harvard.edu/AstroStat/slog/2007/the-last-arxiv-of-2007/feed/ 0 [ArXiv] Spectroscopic Survey, June 29, 2007 http://hea-www.harvard.edu/AstroStat/slog/2007/arxiv-spectroscopic-survey-june-29-2007/ http://hea-www.harvard.edu/AstroStat/slog/2007/arxiv-spectroscopic-survey-june-29-2007/#comments Mon, 02 Jul 2007 22:07:39 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/2007/arxiv-spectroscopic-survey-june-29-2007/ From arXiv/astro-ph:0706.4484

Spectroscopic Surveys: Present by Yip. C. overviews recent spectroscopic sky surveys and spectral analysis techniques toward Virtual Observatories (VO). In addition that spectroscopic redshift measures increase like Moore’s law, the surveys tend to go deeper and aim completeness. Mainly elliptical galaxy formation has been studied due to more abundance compared to spirals and the galactic bimodality in color-color or color-magnitude diagrams is the result of the gas-rich mergers by blue mergers forming the red sequence. Principal component analysis has incorporated ratios of emission line-strengths for classifying Type-II AGN and star forming galaxies. Lyα identifies high z quasars and other spectral patterns over z reveal the history of the early universe and the characteristics of quasars. Also, the recent discovery of 10 satellites to the Milky Way is mentioned.

Spectral analyses take two approaches: one is the model based approach taking theoretical templates, known for its flaws but straightforward extractions of physical parameters, and the other is the empirical approach, useful for making discoveries but difficult in the analysis interpretation. Neither of them has substantial advantage to the other. When it comes to fitting, Chi-square minimization has been dominant but new methodologies are under developing. For spectral classification problems, principal component analysis (Karlhunen-Loeve transformation), artificial neural network, and other machine learning techniques have been applied.

In the end, the author reports statistical and astrophysical challenges in massive spectroscopic data of present days: 1. modeling galaxies, 2. parameterizing star formation history, 3. modeling quasars, 4. multi-catalog based calibration (separating systematic and statistics errors), 5. estimating parameters, which would be beneficial to VO, of which objective is the unification of data access.

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