A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

ADAPTABILITY AND STABILITY OF SOYBEAN GENOTYPES UNDER DIFFERENT TIMES OF SOWING

This study aimed to evaluate the average behavior, the genotype x environment (GxE), adaptability and stability of seven soybean cultivars at three sowing dates in Uberlandia-MG. The tests were conducted at Capim Branco Farm, belonging to the Federal University of Uberlandia. Sowing was held on october 29 (1st season), november 24 (2nd season) and december 17 (3rd season) 2007. The experimental design was a randomized, seven genotypes (UFUS Xavante, UFUS Riqueza, UFUS Guarani, UFUS Milionaria, Msoy 8001, Msoy 8411 and Msoy 8914) with three replications in each of three sowing dates. Means were compared by Tukey test at 5% probability. Analysis of adaptability and phenotypic stability of genotypes was performed using the Eberhart and Russell (1966), Lin and Binns (1988) modified by Carneiro (1998) and centroid (NASCIMENTO et al., 2009). For grain yield, the cultivar UFUS Xavante was classified as specific adaptability to environment and high stability. The other cultivars were classified as being of general adaptability. For oil content, the cultivars Msoy 8914 and UFUS Xavante behaved as high stability and was classified as having high adaptability. For the character content of protein, all cultivars behaved as wide adaptability and low stability.

Outcrossing rate in sweet passion fruit based on molecular markers

P>Yellow and sweet passion fruit are insect-pollinated species native to the tropics. Fruits are used commercially for human consumption worldwide. The yellow passion fruit is an outcrossing species with self-incompatible flowers. However, the reproductive system of the sweet passion fruit (Passiflora alata) has not been well elucidated. The objective of this work was to characterize aspects of the mating system in the sweet passion fruit using random amplified polymorphic DNA (RAPD) and microsatellite markers, particularly the rate of outcrossing in P. alata progenies. A multilocus outcrossing rate of t(m) = 0.994 was determined from RAPD and t(m) = 0.940 from microsatellites, supporting P. alata as an outcrossing species. The fixation indices of the maternal generation (F(m)) were -0.200 and 0.071 with RAPD and microsatellite loci, respectively, indicating the absence of inbreeding in the maternal generation. The paternity correlation (r(p)) varied from -0.008 with RAPD markers to 0.208 with microsatellite markers, suggesting a low probability of finding full sibs within the progenies. The results demonstrated that all progenies assessed in this study were derived from outcrossing.