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, see Deldossi and Nai Ruscone (2020) <doi:10.18637/jss.v094.i02>.

Version: 11.1
Published: 2023-11-14
Author: Marta Nai Ruscone [aut, cre], Laura Deldossi [aut], Cleve Moler [ctb] (LINPACK routines in src), Jack Dongarra [ctb] (LINPACK routines in src)
Maintainer: Marta Nai Ruscone <marta.nairuscone at unige.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: OBsMD citation info
In views: ExperimentalDesign
CRAN checks: OBsMD results

Documentation:

Reference manual: OBsMD.pdf

Downloads:

Package source: OBsMD_11.1.tar.gz
Windows binaries: r-devel: OBsMD_11.1.zip, r-release: OBsMD_11.1.zip, r-oldrel: OBsMD_11.1.zip
macOS binaries: r-release (arm64): OBsMD_11.1.tgz, r-oldrel (arm64): OBsMD_11.1.tgz, r-release (x86_64): OBsMD_11.1.tgz
Old sources: OBsMD archive

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