= Coryn A. L. Bailer-Jones
{c}
<Coryn A. L. Bailer-Jones> developed a statistical treatment of estimating stellar <Euclidean distances> from noisy <stellar parallaxes>. His 2015 analysis showed why simply taking the reciprocal of a measured <parallax> can behave poorly when the fractional uncertainty is appreciable.<Estimating distances from parallaxes by Coryn A. L. Bailer-Jones>[Abstract and section 7: prior choices and an exponentially decreasing space-density model]{ref}
A <Bayesian inference> combines the <parallax> likelihood with a physically chosen distance prior. A positive-distance prior can assign sensible posterior probabilities even to negative measured <parallaxes>; a negative noisy measurement does not imply a negative physical <Euclidean distance>.
Back to article page
