Pattern detection and characterization for astronomical data through probabilistic modelling and statistical inference

Radu Stoica (1, 2) , Shuyan Liu (3) , Lauri Juhan Liivamägi (4, 5) , Enn Saar (6, 5) , Elmo Tempel (5) , Florent Deleflie (1) , Marc Fouchard (1, 2) , Daniel Hestroffer (1) , Irina Kovalenko (1) , Alain Vienne (1, 2)

1 IMCCE - Institut de Mécanique Céleste et de Calcul des Ephémérides
2 Université de Lille, Sciences et Technologies
3 SAMM - Statistique, Analyse et Modélisation Multidisciplinaire (SAmos-Marin Mersenne)
4 Institute of Physics [Tartu]
5 Tartu Observatory
6 Estonian Academy of Sciences

The paper presents several problems coming from astronomy that may be tackled using probability theory and statistics. Due to the nature of data the common question of these problems is what is the pattern hidden in the data. The probabilistic framework allows a statistical and morphological description of these patterns.

Mots clés: spatial Markov models; MCMC simulation; statistical Bayesian inference

Domaines: Statistiques [math.ST]; Instrumentation et méthodes pour l'astrophysique [astro-ph.IM]

Radu Stoica, Shuyan Liu, Lauri Juhan Liivamägi, Enn Saar, Elmo Tempel, et al.. Pattern detection and characterization for astronomical data through probabilistic modelling and statistical inference. the 60th ISI World Statistics Congress, Jul 2015, Rio de Janeiro, Brazil. ⟨hal-01519891⟩