The AstroStat Slog » clusters 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 [ArXiv] 4th week, Apr. 2008 http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-4th-week-apr-2008/ http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-4th-week-apr-2008/#comments Sun, 27 Apr 2008 15:29:48 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/?p=276 The last paper in the list discusses MCMC for time series analysis, applied to sunspot data. There are six additional papers about statistics and data analysis from the week.

  • [astro-ph:0804.2904]M. Cruz et al.
    The CMB cold spot: texture, cluster or void?

  • [astro-ph:0804.2917] Z. Zhu, M. Sereno
    Testing the DGP model with gravitational lensing statistics

  • [astro-ph:0804.3390] Valkenburg, Krauss, & Hamann
    Effects of Prior Assumptions on Bayesian Estimates of Inflation Parameters, and the expected Gravitational Waves Signal from Inflation

  • [astro-ph:0804.3413] N.Ball et al.
    Robust Machine Learning Applied to Astronomical Datasets III: Probabilistic Photometric Redshifts for Galaxies and Quasars in the SDSS and GALEX (Another related publication [astro-ph:0804.3417])

  • [astro-ph:0804.3471] M. Cirasuolo et al.
    A new measurement of the evolving near-infrared galaxy luminosity function out to z~4: a continuing challenge to theoretical models of galaxy formation

  • [astro-ph:0804.3475] A.D. Mackey et al.
    Multiple stellar populations in three rich Large Magellanic Cloud star clusters

  • [stat.ME:0804.3853] C. R\”over , R. Meyer, N. Christensen
    Modelling coloured noise (MCMC & sunspot data)
]]> http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-4th-week-apr-2008/feed/ 0 [ArXiv] 3rd week, Apr. 2008 http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-3rd-week-apr-2008/ http://hea-www.harvard.edu/AstroStat/slog/2008/arxiv-3rd-week-apr-2008/#comments Mon, 21 Apr 2008 01:05:55 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/?p=269 The dichotomy of outliers; detecting outliers to be discarded or to be investigated; statistics that is robust enough not to be influenced by outliers or sensitive enough to alert the anomaly in the data distribution. Although not related, one paper about outliers made me to dwell on what outliers are. This week topics are diverse.

  • [astro-ph:0804.1809] H. Khiabanian, I.P. Dell’Antonio
    A Multi-Resolution Weak Lensing Mass Reconstruction Method (Maximum likelihood approach; my naive eyes sensed a certain degree of relationship to the GREAT08 CHALLENGE)

  • [astro-ph:0804.1909] A. Leccardi and S. Molendi
    Radial temperature profiles for a large sample of galaxy clusters observed with XMM-Newton

  • [astro-ph:0804.1964] C. Young & P. Gallagher
    Multiscale Edge Detection in the Corona

  • [astro-ph:0804.2387] C. Destri, H. J. de Vega, N. G. Sanchez
    The CMB Quadrupole depression produced by early fast-roll inflation: MCMC analysis of WMAP and SDSS data

  • [astro-ph:0804.2437] P. Bielewicz, A. Riazuelo
    The study of topology of the universe using multipole vectors

  • [astro-ph:0804.2494] S. Bhattacharya, A. Kosowsky
    Systematic Errors in Sunyaev-Zeldovich Surveys of Galaxy Cluster Velocities

  • [astro-ph:0804.2631] M. J. Mortonson, W. Hu
    Reionization constraints from five-year WMAP data

  • [astro-ph:0804.2645] R. Stompor et al.
    Maximum Likelihood algorithm for parametric component separation in CMB experiments (separate section for calibration errors)

  • [astro-ph:0804.2671] Peeples, Pogge, and Stanek
    Outliers from the Mass–Metallicity Relation I: A Sample of Metal-Rich Dwarf Galaxies from SDSS

  • [astro-ph:0804.2716] H. Moradi, P.S. Cally
    Time-Distance Modelling In A Simulated Sunspot Atmosphere (discusses systematic uncertainty)

  • [astro-ph:0804.2761] S. Iguchi, T. Okuda
    The FFX Correlator

  • [astro-ph:0804.2742] M Bazarghan
    Automated Classification of ELODIE Stellar Spectral Library Using Probabilistic Artificial Neural Networks

  • [astro-ph:0804.2827]S.H. Suyu et al.
    Dissecting the Gravitational Lens B1608+656: Lens Potential Reconstruction (Bayesian)
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