Linear mixed models are a versatile statistical tool to study data by accounting for fixed effects and random from multiple sources of variability. In many situations, large number candidate is available it interest select parsimonious subset those being effectively relevant predicting the response variable. Variational approximations facilitate fast approximate Bayesian inference parameters va...

Data analysis using the General linear model assumes factors to be fixed effects, and BLUE method, which is based on their mean performance, appropriate select best performing genotypes. The mixed incorporates random effects that are very important compare a genotype’s performance through BLUP. purpose of this study was identify genotypes provided high grain yield model, BLUP BLUE, determine im...

the objectives of this study were to identify a suitable mathematical model for describing the growth curve of baluchi sheep based on monthly records of live weight from birth to yearling; and to evaluate the efficacies of nonlinear mixed effect model (nlmm) and the nonlinear fixed effect model (nlm) methodologies. growth models were fitted to a total of 16,650 weight–age data belonging to 2071...