Practical Guidance for Bayesian Inference in Astronomy

by   Gwendolyn M. Eadie, et al.

In the last two decades, Bayesian inference has become commonplace in astronomy. At the same time, the choice of algorithms, terminology, notation, and interpretation of Bayesian inference varies from one sub-field of astronomy to the next, which can lead to confusion to both those learning and those familiar with Bayesian statistics. Moreover, the choice varies between the astronomy and statistics literature, too. In this paper, our goal is two-fold: (1) provide a reference that consolidates and clarifies terminology and notation across disciplines, and (2) outline practical guidance for Bayesian inference in astronomy. Highlighting both the astronomy and statistics literature, we cover topics such as notation, specification of the likelihood and prior distributions, inference using the posterior distribution, and posterior predictive checking. It is not our intention to introduce the entire field of Bayesian data analysis – rather, we present a series of useful practices for astronomers who already have an understanding of the Bayesian "nuts and bolts" and wish to increase their expertise and extend their knowledge. Moreover, as the field of astrostatistics and astroinformatics continues to grow, we hope this paper will serve as both a helpful reference and as a jumping off point for deeper dives into the statistics and astrostatistics literature.


page 1

page 2

page 3

page 4


Bayesian Synthetic Likelihood

Bayesian statistics is concerned with conducting posterior inference for...

Bayesian inference for misspecified generative models

Bayesian inference is a powerful tool for combining information in compl...

A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas

This paper provides a comprehensive tutorial for Bayesian practitioners ...

Duality between Approximate Bayesian Methods and Prior Robustness

In this paper we show that there is a link between approximate Bayesian ...

Wasserstein Gaussianization and Efficient Variational Bayes for Robust Bayesian Synthetic Likelihood

The Bayesian Synthetic Likelihood (BSL) method is a widely-used tool for...

Combination of Measurement Data and Domain Knowledge for Simulation of Halbach Arrays with Bayesian Inference

Accelerator magnets made from blocks of permanent magnets in a zero-clea...

Core-periphery structure in networks: a statistical exposition

Many real-world networks are theorized to have core-periphery structure ...

Please sign up or login with your details

Forgot password? Click here to reset