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Keywords

astrometry
methods: analytical
methods: data analysis
methods: statistical

How to Cite

The Bayesian Cramér-Rao lower bound in Astrometry. (2018). Revista Mexicana De Astrofísica Y Astronomía Serie De Conferencias, 50, 23-24. https://astronomia.unam.mx/journals/rmxac/article/view/2018rmxac..50...23m
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Abstract

A determination of the highest precision that can be achieved in the measurement of the location of a stellar-like object has been a topic of permanent interest by the astrometric community. The so-called (parametric, or non-Bayesian) Cramér-Rao (CR hereafter) bound provides a lower bound for the variance with which one could estimate the position of a point source. This has been studied recently by Mendez et al. (2013, 2014, 2015). In this work we present a different approach to the same problem (Echeverria et al. 2016), using a Bayesian CR setting which has a number of advantages over the parametric scenario.