pks: Probabilistic Knowledge Structures

Fitting and testing probabilistic knowledge structures, especially the basic local independence model (BLIM, Doignon & Flamagne, 1999) and the simple learning model (SLM), using the minimum discrepancy maximum likelihood (MDML) method (Heller & Wickelmaier, 2013 <doi:10.1016/j.endm.2013.05.145>).

Version: 0.6-0
Depends: R (≥ 3.5.0), stats, sets
Imports: graphics
Suggests: relations, Rgraphviz
Published: 2023-07-07
Author: Florian Wickelmaier [aut, cre], Juergen Heller [aut], Julian Mollenhauer [aut], Pasquale Anselmi [ctb], Debora de Chiusole [ctb], Andrea Brancaccio [ctb], Luca Stefanutti [ctb]
Maintainer: Florian Wickelmaier <wickelmaier at web.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.mathpsy.uni-tuebingen.de/wickelmaier/
NeedsCompilation: no
Citation: pks citation info
Materials: ChangeLog
In views: Psychometrics
CRAN checks: pks results

Documentation:

Reference manual: pks.pdf
Vignettes: Parameter Estimation in Probabilistic Knowledge Structures – Step by Step

Downloads:

Package source: pks_0.6-0.tar.gz
Windows binaries: r-devel: pks_0.6-0.zip, r-release: pks_0.6-0.zip, r-oldrel: pks_0.6-0.zip
macOS binaries: r-release (arm64): pks_0.6-0.tgz, r-oldrel (arm64): pks_0.6-0.tgz, r-release (x86_64): pks_0.6-0.tgz
Old sources: pks archive

Reverse dependencies:

Reverse depends: kstIO
Reverse imports: kstMatrix

Linking:

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