Bayesian inference in quantile functions

Abstract

The role of quantile functions in modeling various forms of statistical data is well established. Generally classical procedures like method of moments, L-moments, percentiles etc are employed in estimating the parameters of the model. In the present work an attempt is made to infer parameters in the Bayesian framework with special emphasis to distributions in which the quantile functions do not posses tractable distribution functions. The procedure is illustrated for some distributions and real life data.

Keywords:

• Quantile function
• Bayes theorem
• prior and posterior quantile functions
• Bayes estimates

Acknowledgements

We thank the referee and the editor for their constructive comments. The second author is thankful to the Department of Science and Technology, Government of India for the financial support under MATRICS scheme.