Presentation is loading. Please wait.

Presentation is loading. Please wait.

Appetizer: Statistical methods in XSPEC

Similar presentations


Presentation on theme: "Appetizer: Statistical methods in XSPEC"— Presentation transcript:

1 Appetizer: Statistical methods in XSPEC
Entrée: A modest proposal on Bayesian methods

2 XSPEC compares data with parametrized theoretical models modified by the instrumental response.
It has been traditional (since the mid-60s) to use c2 to do this comparison and perform frequentist calculation of confidence regions for model parameters. XSPEC does allow different options for the estimator for the variance used as the denominator in c2. As is well known, c2 is not appropriate when there are small numbers of counts in a spectral bin. XSPEC includes the max. likelihood statistic of Cash with an extension to work in the presence of background.

3 Although most X-ray spectroscopy follows the frequentist path, most astronomers then interpret the results in a Bayesian fashion. For those who wish to be more consistent, XSPEC has capabilities to perform Bayesian analysis. It is based on Tom Loredo’s likelihood for a Poisson source in the presence of background. The model parameters can be assigned constant or exponential priors. The posterior pdf can be constructed using Markov Chain Monte Carlo chains.

4 What is required to support widespread use of Bayesian methods in astronomy ?
Is there infrastructure we can put in place which will make it easier to use Bayesian methods ?

5 p(H|D,I) = p(D|H,I) x p(H|I) p(D|I)
Likelihood Prior Posterior

6 The problem is (almost) always what to choose as the prior pdf.
The appropriate part of the statistics literature is full of arguments on how to choose your prior. However, in astronomy the prior pdf is usually the posterior pdf of the previous observation. But in general we don’t save the posterior pdfs and make them publically available.

7 We need a standard file format for probability density functions.
This will provide a method (and incentive) for those performing Bayesian analysis to save their posteriors. These can then be used as input by themselves or others as priors when new data becomes available.

8 Two possible ways of saving pdfs.
A multi-dimensional grid MCMC chain Perhaps need standard file formats for both. Also need considerable thought on what other information should be included to ensure that these pdfs will not be misused.


Download ppt "Appetizer: Statistical methods in XSPEC"

Similar presentations


Ads by Google