[Implementation of the Bayesian statistics in agricultural research and education]
2001
Poldaru, R. | Roots, J. (Estonian Agricultural Univ., Tartu (Estonia))
Advances in computers and numerical methods have made it possible to implement Bayesian analysis previously considered infeasible. The limitations of traditional statistical methods are part of the reason for the new popularity of this approach. Bayesian methods have increased in popularity over the past decade, in large part due to advances in statistical computing that allow the evaluation of complex posterior distributions using Markov chain Monte Carlo (MCMC) integration methods. The new tools have made the Bayesian approach accessible to a wide range of users, who say it has significant advantages. In this paper implementation of Bayesian methods in the Estonian Agricultural University (Institute of Informatics) is considered and the possibilities of Bayesian methods in agricultural research and education are discussed.
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