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Informative Versus Non-Informative Prior Distributions and their Impact on the Accuracy of Bayesian Inference

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  • Grzenda Wioletta

    (Warsaw School of Economics, Collegium of Economic Analysis, Institute of Statistics and Demography, ; Warsaw, ; Poland)

Abstract

In this study the benefits arising from the use of the Bayesian approach to predictive modelling will be outlined and exemplified by a linear regression model and a logistic regression model. The impact of informative and non-informative prior on model accuracy will be examined and compared. The data from the Central Statistical Office of Poland describing unemployment in individual districts in Poland will be used. Markov Chain Monte Carlo methods (MCMC) will be employed in modelling.

Suggested Citation

  • Grzenda Wioletta, 2016. "Informative Versus Non-Informative Prior Distributions and their Impact on the Accuracy of Bayesian Inference," Statistics in Transition New Series, Polish Statistical Association, vol. 17(4), pages 763-780, December.
    • Handle: RePEc:vrs:stintr:v:17:y:2016:i:4:p:763-780:n:1
    DOI: 10.21307/stattrans-2016-051
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