ESTIMATE OF THE HYPSOMETRIC RELATIONSHIP WITH NONLINEAR MODELS FITTED BY EMPIRICAL BAYESIAN METHODS

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Monica Fabiana Bento Moreira Cláudio Roberto Thiersch Marinho Gomes de Andrade José Roberto Soares Scolforo

Abstract

In this paper we propose a Bayesian approach to solve the inference problem with restriction on parameters, regarding to nonlinear models used to represent the hypsometric relationship in clones of Eucalyptus sp. The Bayesian estimates are calculated using Monte Carlo Markov Chain (MCMC) method. The proposed method was applied to different groups of actual data from which two were selected to show the results. These results were compared to the results achieved by the minimum square method, highlighting the superiority of the Bayesian approach, since this approach always generate the biologically consistent results for hipsometric relationship.

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How to Cite
MOREIRA, Monica Fabiana Bento et al. ESTIMATE OF THE HYPSOMETRIC RELATIONSHIP WITH NONLINEAR MODELS FITTED BY EMPIRICAL BAYESIAN METHODS. CERNE, [S.l.], v. 21, n. 3, p. 405-411, apr. 2016. ISSN 2317-6342. Available at: <http://cerne.ufla.br/site/index.php/CERNE/article/view/1086>. Date accessed: 16 sep. 2019.
Keywords
Restriction parameters, Bayesian inference, forest measurement.
Section
Article