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.

Nai Ruscone, M., Deldossi, L., OBSMD: AN R-PACKAGE FOR OBJECTIVE BAYESIANMODEL DISCRIMINATION IN FOLLOW-UP DESIGNS, in Proceedings SCo 2013, (Milano, 09-12 September 2013), Poliscript 2013, Milano 2013: 1-4 [http://hdl.handle.net/10807/53362]

OBSMD: AN R-PACKAGE FOR OBJECTIVE BAYESIAN MODEL DISCRIMINATION IN FOLLOW-UP DESIGNS

Nai Ruscone, Marta;Deldossi, Laura
2013

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.
Inglese
Proceedings SCo 2013
SCo 2013
Milano
9-set-2013
12-set-2013
97888-6493-019-0
Nai Ruscone, M., Deldossi, L., OBSMD: AN R-PACKAGE FOR OBJECTIVE BAYESIANMODEL DISCRIMINATION IN FOLLOW-UP DESIGNS, in Proceedings SCo 2013, (Milano, 09-12 September 2013), Poliscript 2013, Milano 2013: 1-4 [http://hdl.handle.net/10807/53362]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/53362
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