A recent arXival by Spencer et al. presents a Bayesian analysis of radial velocity data for the binary fraction in (the ultra faint dwarf galaxy) Leo II in which the inference proceeds by comparison of mock datasets against the observed data. In this particular case the methodology ends up corresponding to a Bayesian indirect inference algorithm (e.g. Drovandi et al., Creel et al.) in which the summary statistic is the counts in bins of the beta statistic (observational error weighted squared pairwise difference between radial velocities in consecutive observations) and its auxiliary model is the skewed Normal (independent across bins). In principle one could perform an ordinary Bayesian analysis of this data under a hierarchical model (which would also yield predictions for the binarity or otherwise of each star in the sample) but fitting might (? relative to the potential for contraction of the posterior) be overly time consuming due to the dimensionality and shape of the joint posterior. Instead the indirect inference approach here is straightforwards to implement targeting the binary fraction directly, and a further set of input-output simulations reassure that the posterior median is effectively an unbiased estimator for the true binary fraction.

- Follow Another Astrostatistics Blog on WordPress.com
### View Posts by Category

ABC Astronomy Astrostatistics Bad Science Big Data Bayes Dirichlet Processes Fourier analysis Gaussian Processes Infinite-Dimensional Inference INLA Marginal Likelihood Estimation Measure Theory Non-Parametric Order Statistics Particle MCMC Quantile Regression Rants Semi-Parametric Statistics Uncategorized Zoology, Epidemiology, & Clinical Trials### Archive

- October 2017
- August 2017
- July 2017
- June 2017
- May 2017
- April 2017
- March 2017
- February 2017
- January 2017
- December 2016
- November 2016
- October 2016
- September 2016
- August 2016
- July 2016
- March 2016
- February 2016
- January 2016
- December 2015
- October 2015
- September 2015
- August 2015
- July 2015
- June 2015
- May 2015
- April 2015
- March 2015
- February 2015
- January 2015
- December 2014
- November 2014
- October 2014
- September 2014
- August 2014
- July 2014
- June 2014
- May 2014
- April 2014
- March 2014
- February 2014
- January 2014
- December 2013
- November 2013
- October 2013
- September 2013
- August 2013
- July 2013
- June 2013
- May 2013
- April 2013

Advertisements