R Package OBsMD for Follow-Up Designs in an Objective Bayesian Framework

R Package OBsMD for Follow-Up Designs in an Objective Bayesian Framework

Bayesian design of experiments, screening experiments, Bayesian model selection,
model discrimination

Fractional factorial experiments often produce ambiguous results due to confounding
among the factors; as a consequence more than one model is consistent with the data.
Thus, the practical problem is how to choose additional runs in order to discriminate
among the rival models and to identify the active factors. The R package OBsMD solves
this problem by implementing the objective Bayesian methodology proposed by Consonni
and Deldossi (2016). The main feature of this approach is that the follow-up designs are
obtained through the use of just two functions, OBsProb() and OMD() without requiring
any prior specifications, being fully automatic. Thus OBsMD provides a simple tool for
conducting a design of experiments to solve real world problems.

Laura Deldossi

https://www.jstatsoft.org/article/view/v094i02

Universitá Cattolica del Sacro Cuore

June 2020

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