A sensorimotor paradigm for Bayesian model selection

A sensorimotor paradigm for Bayesian model selection

Sensorimotor control is thought to rely on predictive internal models in order to cope efficiently with uncertain environments. Recently, it has been shown that humans not only learn different internal models for different tasks, but that they also extract common structure between tasks. This raises the question of how the motor system selects between different structures or models, when each m...

Bayesian paradigm for analysing count data in longitudina studies using Poisson-generalized log-gamma model

In analyzing longitudinal data with counted responses, normal distribution is usually used for distribution of the random efffects. However, in some applications random effects may not be normally distributed. Misspecification of this distribution may cause reduction of efficiency of estimators. In this paper, a generalized log-gamma distribution is used for the random effects which includes th...

A fuzzy-Bayesian model for supplier selection

The selection supplier problem has received a lot of attention from academics in recent years. Several models were developed in the literature, combining consolidated operations research and artificial intelligence methods and techniques. However, the tools presented in the literature neglected learning and adaptation, since this decision making process is approached as a static one rather than...

A Bayesian Model for Morpheme and Paradigm Identification

A Bayesian Paradigm for Dynami