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

• Autorzy: Wioletta Grzenda
• Języki publikacji: EN

Abstrakty

EN

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 noninformative 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. (original abstract)

Słowa kluczowe

EN

Regression models; Bayesian inference; Monte Carlo method; Unemployment

PL

Modele regresji; Wnioskowanie bayesowskie; Metoda Monte Carlo; Bezrobocie

• Czasopismo: Statistics in Transition
• Rocznik: 2016
• Tom: 17
• Numer: nr 4
• Strony: 763--780

Twórcy

autor

Wioletta Grzenda

• Warsaw School of Economics, Poland

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