Practical Bayesian data analysis involves manipulating and summarizing simulations from the posterior distribution of the unknown parameters. By manipulation we mean computing posterior distributions of functions of the unknowns, and generating posterior predictive distributions. The results need to be summarized both numerically and

The independent additive errors linear model consists of a structure for the mean and a separate structure for the error distribution. The error structure may be parametric or it may be semiparametric. Under alternative values of the mean structure, the best fitting additive errors model has an error distribution which can be represented as the convolution of the actual error distribution and t...

Aporocotyle mariachristinae n. sp. and A. ymakara Villalba & Fernández, 1986 were collected from the bulbus arteriosus and ventral aorta of pink cusk-eels, Genypterus blacodes (Forster, 1801) from Patagonia, Argentina. A. mariachristinae n. sp. can be distinguished from all the species of Aporocotyle by the asymmetrical extension of posterior caeca (right posterior caecum longer, terminating at...

The way in which memories decline over time has been studied for over a century, but remains an unresolved issue because of a lack of sufficiently precise data and effective model selection techniques. Here we address this gap with a particular focus on whether the decline in memory retention is complete or asymptotes above chance performance. We collected stem cued recall and stem completion d...

INTRODUCTION In our experience, sometimes, the symptom of patients who suffered from infarction in internal capsule (IC) do not necessarily fit the classical fiber distribution. This study aims to explain this phenomenon. METHODS AND MATERIALS A total of 34 patients with infarction lesions in the IC were included in this study, according to the clinical symptom, divided into three groups, gro...