OBsMD: Objective Bayesian Model Discrimination in Follow-Up Designs

Implements the objective Bayesian methodology proposed in Consonni and Deldossi in order to choose the optimal experiment that better discriminate between competing models. G.Consonni, L. Deldossi (2014) Objective Bayesian Model Discrimination in Follow-up Experimental Designs, Test. <doi:10.1007/s11749-015-0461-3>.

Version: 2.1
Published: 2018-01-22
Author: Laura Deldossi and Marta Nai Ruscone based on Daniel Meyer's code (2016)
Maintainer: Marta Nai Ruscone <mnairuscone at liuc.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: ExperimentalDesign
CRAN checks: OBsMD results

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Reference manual: OBsMD.pdf
Package source: OBsMD_2.1.tar.gz
Windows binaries: r-devel: OBsMD_2.1.zip, r-release: OBsMD_2.1.zip, r-oldrel: OBsMD_2.1.zip
OS X binaries: r-release: OBsMD_2.1.tgz, r-oldrel: OBsMD_2.1.tgz
Old sources: OBsMD archive

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