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Article | 06-July-2017

INFORMATIVE VERSUS NON-INFORMATIVE PRIOR DISTRIBUTIONS AND THEIR IMPACT ON THE ACCURACY OF BAYESIAN INFERENCE

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.

Wioletta Grzenda

Statistics in Transition New Series, Volume 17 , ISSUE 4, 763–780

Article | 05-September-2021

Bayesian estimation and prediction based on Rayleigh record data with applications

Based on a record sample from the Rayleigh model, we consider the problem of estimating the scale and location parameters of the model and predicting the future unobserved record data. Maximum likelihood and Bayesian approaches under different loss functions are used to estimate the model’s parameters. The Gibbs sampler and Metropolis-Hastings methods are used within the Bayesian procedures to draw the Markov Chain Monte Carlo (MCMC) samples, used in turn to compute the Bayes estimator

Raed R. Abu Awwad, Omar M. Bdair, Ghassan K. Abufoudeh

Statistics in Transition New Series, Volume 22 , ISSUE 3, 59–79

Article | 20-December-2020

A Bayesian analysis of complete multiple breaks in a panel autoregressive (CMB-PAR(1)) time series model

Varun Agiwal, Jitendra Kumar, Dahud Kehinde Shangodoyin

Statistics in Transition New Series, Volume 21 , ISSUE 5, 133–149

Sampling Methods | 25-May-2018

A BAYESIAN INFERENCE OF MULTIPLE STRUCTURAL BREAKS IN MEAN AND ERROR VARIANCE IN PANEL AR (1) MODEL

Varun Agiwal, Jitendra Kumar, Dahud Kehinde Shangodoyin

Statistics in Transition New Series, Volume 19 , ISSUE 1, 7–23

Article | 15-March-2019

BAYESIAN SPATIAL ANALYSIS OF CHRONIC DISEASES IN ELDERLY CHINESE PEOPLE USING A STAR MODEL

Ping Gao, Hikaru Hasegawa

Statistics in Transition New Series, Volume 19 , ISSUE 4, 645–670

Research Communicate | 27-May-2018

SOME RESULTS FROM THE 2013 INTERNATIONAL YEAR OF STATISTICS

Jan Kordos

Statistics in Transition New Series, Volume 19 , ISSUE 1, 149–158

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