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: 6.1
Published: 2020-06-25
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
CRAN checks: OBsMD results

Downloads:

Reference manual: OBsMD.pdf
Package source: OBsMD_6.1.tar.gz
Windows binaries: r-devel: OBsMD_6.1.zip, r-devel-UCRT: OBsMD_6.1.zip, r-release: OBsMD_6.1.zip, r-oldrel: OBsMD_6.1.zip
macOS binaries: r-release: OBsMD_6.1.tgz, r-oldrel: OBsMD_6.1.tgz
Old sources: OBsMD archive

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