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We have tested for luminosity, colour and morphology dependence of the degree of filamentarity in seven nearly two dimensional strips from the Sloan Digital Sky Survey Data Release Four (SDSS DR4). The analysis is carried out at various…

Astrophysics · Physics 2009-11-11 Biswajit Pandey , Somnath Bharadwaj

We present canonical quantiles and depths for directional data following a distribution which is elliptically symmetric about a direction $\mu$ on the sphere $\mathcal{S}^{d-1}$. Our approach extends the concept of Ley et al. [1], which…

Statistics Theory · Mathematics 2022-10-13 Konstantin Hauch , Claudia Redenbach

Stage-IV dark energy wide-field surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will observe an unprecedented number density of galaxies. As a result, the majority of imaged galaxies will visually…

Instrumentation and Methods for Astrophysics · Physics 2026-03-13 Ismael Mendoza , Derek Hansen , Runjing Liu , Zhe Zhao , Ziteng Pang , Axel Guinot , Camille Avestruz , Jeffrey Regier , the LSST Dark Energy Science Collaboration

Information extracted from the GAIA Data Release 3 is used to examine the stellar contents within projected separations of 10 parsecs from eight close binary systems that are either classical W Serpentis systems or related objects. The goal…

Solar and Stellar Astrophysics · Physics 2023-04-12 T. J. Davidge

The well-known Bayes theorem assumes that a posterior distribution is a probability distribution. However, the posterior distribution may no longer be a probability distribution if an improper prior distribution (non-probability measure)…

Instrumentation and Methods for Astrophysics · Physics 2018-08-28 Hyungsuk Tak , Sujit K. Ghosh , Justin A. Ellis

This paper addresses the problem of summarizing the posterior distributions that typically arise, in a Bayesian framework, when dealing with signal decomposition problems with unknown number of components. Such posterior distributions are…

Computation · Statistics 2011-11-29 Alireza Roodaki , Julien Bect , Gilles Fleury

Machine learning holds tremendous promise for transforming the fundamental practice of scientific discovery by virtue of its data-driven nature. With the ever-increasing stream of research data collection, it would be appealing to…

Machine Learning · Computer Science 2024-03-06 Jianan Fan , Dongnan Liu , Hang Chang , Heng Huang , Mei Chen , Weidong Cai

We report the results of a multi-waveband analysis of the masses and luminosities of $\sim$600 galaxy groups and clusters identified in the maxBCG catalogue. These data are intended to form the basis of future work on the formation of the…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-24 Robert N. Proctor , Claudia Mendes de Oliveira , Luiz Azanha , Renato Dupke , Roderik Overzier

The disks of spiral galaxies are generally elliptical rather than circular. The distribution of ellipticities can be fit with a log-normal distribution. For a sample of 12,764 galaxies from the Sloan Digital Sky Survey Data Release 1 (SDSS…

Astrophysics · Physics 2009-11-10 Barbara S. Ryden

We consider Bayesian estimation of a $p\times p$ precision matrix, when $p$ can be much larger than the available sample size $n$. It is well known that consistent estimation in such ultra-high dimensional situations requires regularization…

Statistics Theory · Mathematics 2014-11-07 Sayantan Banerjee , Subhashis Ghosal

We present a new catalogue of 55,121 groups and clusters centred on Luminous Red Galaxies from SDSS DR7 in the redshift range 0.15<z<0.4. We provide halo mass estimates for each of these groups derived from a calibration between the optical…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 J. M. Budzynski , S. Koposov , I. G. McCarthy , S. L. McGee , V. Belokurov

This paper presents the dynamical simulations run in the potential derived from the light distribution of 5 late-type barred spiral galaxies. The aim is to determine whether the mass distribution together with the hydrodynamical simulations…

Astrophysics · Physics 2009-11-10 I. Pérez , R. Fux , K. Freeman

We present a new method for image salience prediction, Clustered Saliency Prediction. This method divides subjects into clusters based on their personal features and their known saliency maps, and generates an image salience model…

Computer Vision and Pattern Recognition · Computer Science 2023-11-06 Rezvan Sherkati , James J. Clark

We analyse a set of new pencil-beam galaxy redshift data in three small regions around the South Galactic Pole (SGP) area. We investigate whether we can find any evidence of the quasi-periodic peaks discovered by Broadhurst et al. (1990) in…

Astrophysics · Physics 2015-06-24 S. Ettori , L. Guzzo , M. Tarenghi

(Abridged) We study predictions for galaxy cluster observables that can test the statistics of dark matter halo shapes expected in a flat LCDM universe. We present a simple analytical model for the prediction of cluster-scale X-ray…

We develop and describe a Bayesian statistical analysis to solve the surface brightness equations for Cepheid distances and stellar properties. Our analysis provides a mathematically rigorous and objective solution to the problem, including…

Astrophysics · Physics 2009-11-07 T. G. Barnes , W. H. Jefferys , J. O. Berger , P. J. Mueller , K. Orr , R. Rodriguez

We propose an algebraic and a geometric classification of euclidean isodual lattices of fixed rank. First, we prove that these lattices are distribued according to a finite number of algebraic types. Second, we show that they are…

Number Theory · Mathematics 2014-11-11 Christophe Bavard

This paper studies Bayesian variable selection in linear models with general spherically symmetric error distributions. We propose sub-harmonic priors which arise as a class of mixtures of Zellner's g-priors for which the Bayes factors are…

Methodology · Statistics 2013-03-12 Yuzo Maruyama , William E. Strawderman

Circular and non-flat data distributions are prevalent across diverse domains of data science, yet their specific geometric structures often remain underutilized in machine learning frameworks. A principled approach to accounting for the…

Methodology · Statistics 2025-09-25 Thibault de Surrel , Fabien Lotte , Sylvain Chevallier , Florian Yger

Neural demyelination and brain damage accumulated in white matter appear as hyperintense areas on T2-weighted MRI scans in the form of lesions. Modeling binary images at the population level, where each voxel represents the existence of a…

Methodology · Statistics 2023-05-29 Anna Menacher , Thomas E. Nichols , Chris Holmes , Habib Ganjgahi