Please use this identifier to cite or link to this item: http://arl.liuc.it/dspace/handle/2468/4067
Title: OBsMD: an R package for objective Bayesian model discrimination in follow-up design
Authors: Deldossi, Laura
Nai Ruscone, Marta
Issue Date: 2013
Bibliographic citation: Deldossi Laura, Nai Ruscone Marta (2013), OBsMD: an R package for objective Bayesian model discrimination in follow-up design. In: Sco 2013: proceedings of the 8th complex data modeling and computationally intensive statistical methods for estimation and prediction, Milano, Italy.
Abstract: Occasionally screening designs do not lead to unequivocal conclusions regarding which combinations of factors (models) are active. From a Bayesian viewpoint, this means that the posterior distribution on model space will be fairly evenly spread out over a few models. In these circumstances, a follow-up design is needed, the aim being of choosing extra runs in order to solve, or at least alleviate, this ambiguity. This R-package OBsMD implements the objective Bayesian methodology developed in Consonni and Deldossi (2013) for this scope.
URI: http://arl.liuc.it/dspace/handle/2468/4067
Journal/Book: Sco 2013: proceedings of the 8th complex data modeling and computationally intensive statistical methods for estimation and prediction, Milano, Italy
ISBN: 978-88-6493-019-0
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