Modelos de regressão com efeitos mistos aplicados a dados de germinação de sementes

• Autor(a) principal: Pereira, Edilenia Queiroz
• Data de Publicação: 2017
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da Universidade Estadual de Maringá (RI-UEM)
• Texto Completo: http://repositorio.uem.br:8080/jspui/handle/1/4366
• topic: Stevia rebaudiana (Bert) Bertoni; Modelo GAMLSS; Stevia rebaudiana (Bert) Bertoni; Razão de Chance; Stevia rebaudiana (Bert) Bertoni; Germinação de sementes; Modelos; Bioestatística; Stevia rebaudiana (Bert) Bertoni; Brasil.; Model GAMLSS; Odds ratio,Stevia rebaudiana; Brazil.; Ciências Exatas e da Terra; Estatística

Stevia rebaudiana is a plant that has great potential when it comes to the production of natural sweeteners, this fact produces a great economic and scientific interest in relation to its characteristics and therapeutic properties, which are present in great majority in its sheets. Interested in understanding the germination behavior of Stevia rebaudiana seeds under controlled conditions, researchers from the Experimental Farm of Iguatemi conducted an experiment with 9,600 seeds taken from four different lots and submitted to light and position effects Within the germinator us. In order to analyze these data, we used the generalized linear mixed regression models with Binomial distribution, Beta-binomial with frequentist approach and Bayesian approach and the Multinomial distribution with frequentist approach. The estimation and validation of the adjusted models were performed by the frequentist package "gamlss" and by Bayesian package "INLA" of the statistical environment R. The logit link function was used in all fitted models and the choice of the Final model was given by means of AIC, BIC and Deviance Global measurements from the frequentist point of view and DIC, WAIC and LPML from the Bayesian point of view. By the criteria of selection of models it was noticed that the Binomial and Beta-binomial models did not present difference in relation to the quality of the obtained results, being thus equivalent, both by frequentist point of view as Bayesian. The methodology used was adequate in explaining the germination, in relation to the factors of influence or explanatory variables, namely light, position, lot and germinator. Based on the adjusted models it was possible to identify that there is no difference in seed germination among the four germinators used. On the other hand, both the type of light applied and the position in which these seeds are placed inside the germinators have been influencing the germination results of the seeds.