Assessing the external stochastic errors of radio source position catalogues derived from VLBI observations is important for tasks such as estimating the quality of the catalogues and their weighting during combination. One of the widely used methods to estimate these errors is the three-cornered-hat technique, which can be extended to the N-cornered-hat technique. A critical point of this method is how to properly account for the correlations between the compared catalogues. We present a new approach to solving this problem that is suitable for simultaneous investigations of several catalogues. To compute the correlation between two catalogues A and B, the differences between these catalogues and a third arbitrary catalogue C are computed....
We describe a probabilistic method of cross-identifying astrophysical sources in two catalogs from t...
International audienceAims. In this study, we compare several methods of modeling large-scale system...
We consider the statistical problem of catalogue matching from a machine learning perspective with t...
Assessing the external stochastic errors of radio source position catalogues derived from VLBI obser...
ABSTRACT. In this paper, a new method of investigation of the external radio source position catalog...
In this paper four methods of the representing RSC systematic differences have been examined by comp...
Context.Radio source catalogues (RSCs) obtained from very long baseline interferometry (VLBI) observ...
Aims. We propose to estimate the accuracy of current very long baseline interferometry (VLBI) catalo...
Context. Radio source catalogues (RSCs) obtained from very long baseline interferometry (VLBI) obser...
A new approach to the assessment of stochastic errors of radio source position catalogue
International audienceWe describe a probabilistic method of cross-identifying astrophysical sources ...
International audienceContext. Catalogue cross-correlation is essential to building large sets of mu...
We describe a probabilistic method of cross-identifying astrophysical sources in two catalogs from t...
Abstract. In 2007, a joint IERS/IVS Working Group has been estab-lished to consider practical issues...
The two-point correlation function of the galaxy distribution is a key cosmological observable that ...
We describe a probabilistic method of cross-identifying astrophysical sources in two catalogs from t...
International audienceAims. In this study, we compare several methods of modeling large-scale system...
We consider the statistical problem of catalogue matching from a machine learning perspective with t...
Assessing the external stochastic errors of radio source position catalogues derived from VLBI obser...
ABSTRACT. In this paper, a new method of investigation of the external radio source position catalog...
In this paper four methods of the representing RSC systematic differences have been examined by comp...
Context.Radio source catalogues (RSCs) obtained from very long baseline interferometry (VLBI) observ...
Aims. We propose to estimate the accuracy of current very long baseline interferometry (VLBI) catalo...
Context. Radio source catalogues (RSCs) obtained from very long baseline interferometry (VLBI) obser...
A new approach to the assessment of stochastic errors of radio source position catalogue
International audienceWe describe a probabilistic method of cross-identifying astrophysical sources ...
International audienceContext. Catalogue cross-correlation is essential to building large sets of mu...
We describe a probabilistic method of cross-identifying astrophysical sources in two catalogs from t...
Abstract. In 2007, a joint IERS/IVS Working Group has been estab-lished to consider practical issues...
The two-point correlation function of the galaxy distribution is a key cosmological observable that ...
We describe a probabilistic method of cross-identifying astrophysical sources in two catalogs from t...
International audienceAims. In this study, we compare several methods of modeling large-scale system...
We consider the statistical problem of catalogue matching from a machine learning perspective with t...