2 resultados para Maximum pseudo-likelihood
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
The objective of this study was to evaluate the genetic differences among three matrix groups of Cedrela fissilis based on quantitative juvenile variables on a progeny test to define seed collecting zones and use of seeds of this species in the study region as well as to evaluate genetic variability of the sampled material. A progeny test was established in a nursery with seeds from 48 seed trees collected in the municipalities of Rio Negrinho, Mafra and Sao Bento do Sul, state of Santa Catarina, and in the municipalities of Lapa, Rio Negro, Campo do Tenente and Antonio Olinto, state of Parana. Of the collected seed trees, 33 sampled trees were distributed in three sites and 15 trees were dispersed in the studied region. It was used a complete random block design, with 8 replicates and 20 plants per plot. Evaluated data included: emergency rate; seedling base diameter and height (61, 102 and 145 days after the seeds were sowed); seedling survival; number of leaves per seedling; aerial section dry mass and root dry mass; and the foliar area of the third fully expanded leaf measured from the apical meristem. The Maximum Restricted Likelihood Method (REML) was used, using the software SELEGEN for analysis. It was found that the juvenile characters are strongly genetically controlled and they can be used to estimate genetic variability of population samples of Cedrela fissilis. The three groups of trees spatially limited did not significantly differ among each other, allowing to conclude that the three areas are part of the same tree seed transfer zone.
Resumo:
In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.