Comparison of Normal, Logistic, Laplace, and Student’s t distributions for experimental error in the Bayesian description of dry matter accumulation in Allium sativum
George Lucas Santana de Moura,
Felipe Guzzo,
Paulo Roberto Cecon
et al.
Abstract:This study assessed distributions associated with Bayesian nonlinear modeling error in the description of total plant dry matteraccumulation (TDMA) of Allium sativumas a function of days after planting (DAP). According to the DIC criterion, Logistic and Gompertzmodels that use student’s t distribution error exhibited the highest DIC with logistic error distribution. In general, the difference of DIC in all the scenarios was not more than 5.The Bayes factor (BF) criterion showed no difference in the Logistic an… Show more
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