Analysis of (radio) spectra

The is the main page for code for Bayesian analysis of radio spectra and similar observational data.

Introduction

Observed radio spectra often consist of few measurements (typically 3–10) with significant errors against which it is tempting to try to fit a number of different models. A Bayesian approach realised using the nested sampling algorithms allows:

  • objective selection between the available models
  • a mechanism to introduce prior information (e.g., constraints on total luminosity, maximum slope of power-law like components, etc)
  • full probability distribution of model parameters, not just a point estimate with symmetric error

Where can I find out more?

The method is described in the paper Paper I: Method. There are forthcoming papers with application of the approach and the software to ULIRGS, radio-galaxies and near-by galaxies.

Summary of version history

RNested

It is recommended to use the R re-implementation, which is detailed at on RNested – Nested Sampling in R & analysis of spectra. page.

Version 1.0

This is the first version applied to original observations and used to make physical conclusions.

Version 0.1

This is the first public release of the library, arXiv:0912.2317