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By Roberto Trotta (auth.), Luis Manuel Sarro, Laurent Eyer, William O'Mullane, Joris De Ridder (eds.)

​​​​​ ​This quantity presents an summary of the sector of Astrostatistics understood because the sub-discipline devoted to the statistical research of astronomical info. It offers examples of the applying of some of the methodologies now to be had to present open matters in astronomical examine. The technical elements relating to the medical research of the impending petabyte-scale databases are emphasised given the significance that scalable wisdom Discovery options can have for the complete exploitation of those databases.

Based at the 2011 Astrostatistics and knowledge Mining in huge Astronomical Databases convention and faculty, this quantity gathers examples of the paintings by way of top authors within the components of Astrophysics and statistics, together with an important contribution from many of the groups that ready for the processing and research of the Gaia information.

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In particular, in highdensity regions (≥105 sources per degree2), the effective magnitude limit may be brighter or the number of observations per source smaller than the average. The statistical description and analysis of the varying completeness of the Gaia catalogue will be a delicate issue to deal with. Correlated errors In general, the errors of the astrometric parameters for a given source will not be statistically independent. Moreover, the errors for different sources may also be correlated.

The third proposal is clearly the most ambitious and will require a lot of research into how such an interface to the likelihood function can be practically realized and maintained (much computing power will be involved). Possibly the only way to make the complicated Gaia likelihood function available is through publication of the processing software which was used (parts of which are based on forward modelling). However, a major change in the attitude of users toward a “catalogue” is required.

Sorrentino SVM + phot-z et al. + Kewley line MLP Seyferts vs. Liners SDSS phot. BPT plot + SVM + phot-z Heckman and Kewley lines MLP 76% etype2 =86% Type 2 = 100% etype1 =99% etype2 =98% 78% Seyfert ∼ 53% Liners ∼ 92% 80% Cross validation of results and “folding” (5 subsets) of the data set were used for all experiments. The goal of the experiments was conservative since we were not interested in completeness but rather in minimizing the fraction of false positives. Three experiments were performed.

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