It’s Friday afternoon but before I collapse, exhausted, into the arms of the weekend I’ll take the opportunity to announce yet another new paper at the Open Journal of Astrophysics.
The latest paper is the 45th so far in Volume 6 (2023) – just five to go for a half-century – and it’s the 110th altogether. This one was actually published on Tuesday November 14th.
The title is “Marginalised Normal Regression: Unbiased curve fitting in the presence of x-errors” and it’s by Deaglan J. Bartlett (Institut d’Astrophysique de Paris, France) and Harry Desmond (Portsmouth, UK). It sounds like a statistical methods paper, and indeed it is, but remember that there’s a very long historical connection between astronomy and the development of statistical methods for data analysis, and this paper tackles a very longstanding issue: how best to fit curves in the presence of noisy data. This paper presents a new method for doing this, together with applications to cosmological and astrophysical data, and accompanying software. It is in the folder marked Instrumentation and Methods for Astrophysics.
Here is the overlay of the paper containing the abstract:
You can click on the image of the overlay to make it larger should you wish to do so. You can find the officially accepted version of the paper on the arXiv here.
In the Dark 