Recent studies have uncovered remarkable variation in paternity within primate groups. To date, however, we lack a general understanding of the factors that drive variation in paternity skew among primate groups and across species. Our study focused on hypotheses from reproductive skew theory involving limited control and the use of paternity "concessions" by investigating how paternity covarie...

introduction: food consumption patterns are changing as a result of health and environmental issues. subsequently, farmers are under increasing pressure to develop and utilize less toxic production methods and pest control. organic agriculture is a production system that sustains the health of soils, ecosystems, and people. it relies on ecological processes, biodiversity, and cycles adapted to ...

Discriminant analysis is a widely used multivariate technique with Fisher’s discriminant analysis (FDA) being its most venerable form. FDA assumes equality of population covariance matrices, but does not require multivariate normality. Nevertheless, the latter is desirable for optimal classification. To test FDA's performance under non-normality caused by skewness the method was assessed with s...

The assumption of normality in data has been considered in the field of statistical analysis for a long time. However, in many practical situations, this assumption is clearly unrealistic. It has recently been suggested that the use of distributions indexed by skewness/shape parameters produce more flexibility in the modelling of different applications. Consequently, the results show a more rea...

We consider regularization of the parameters in multivariate linear regression models with the errors having a multivariate skew-t distribution. An iterative penalized likelihood procedure is proposed for constructing sparse estimators of both the regression coefficient and inverse scale matrices simultaneously. The sparsity is introduced through penalizing the negative log-likelihood by adding...

A fast and simple method is proposed that produces approximate multivariate local D-optimal designs of high e¢ ciency for models with binary response. The method assumes availability of a D-optimal design for a parallel normal response linear problem that has the same linear predictor, with an assumption of homogenous variance; the change required to transform the standard design into an e¢ cie...

Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-lognormal random effects model, a two-part logit-truncated normal random effects model, a two-pa...