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The Bayesian approach is increasingly becoming popular among the astrophysics data analysis communities. However, the Pakistan statistics communities are unaware of this fertile interaction between the two disciplines. Bayesian methods have been in use to address astronomical problems since the very birth of the Bayes probability in eighteenth century. Today the Bayesian methods for the detection and parameter estimation of gravitational waves have solid theoretical grounds with a strong promise for the realistic applications. This article aims to introduce the Pakistan statistics communities to the applications of Bayesian Monte Carlo methods in the analysis of gravitational wave data with an  overview of the Bayesian signal detection and estimation methods and demonstration by a couple of simplified examples.


Bayesian inference MCMC gravitational wave detection and estimation

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Author Biography

Asad Ali, Department of Space Science Institute of Space Technology Islamabad 44000, Pakistan

I am a graduate of Department of Statistics, The University of Auckland, New Zealand. I had my PhD under the supervision of Prof Renate Meyer (New Zealand) and Prof Dr Nelson Christensen (Carleton College USA). I worked on a NASA project called Laser Interferometer Antenna (LISA) for gravitational wave detection. I applied Bayesian inference with advanced Markov chain Monte Carlo for the detection and paraeter estimation of gravitational wave soures.

Currently I am Assistant Professor at Department of Space, Institutte of Space Technology Islamabad. I teach Gravitational wave data analysis to MS/PhD astronomy and astrophysics and Spatial and Geostatsics to MS/PhD GIS&RS.  

How to Cite
Ali, A., Ahmad, S., Nawaz, M., Ullah, S., & Aqeel, M. (2015). Bayesian Inference on Gravitational Waves. Pakistan Journal of Statistics and Operation Research, 11(4), 645-665.