Package: pks 0.6-1
Florian Wickelmaier
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>).
Authors:
pks_0.6-1.tar.gz
pks_0.6-1.tar.gz(r-4.5-noble)pks_0.6-1.tar.gz(r-4.4-noble)
pks_0.6-1.tgz(r-4.4-emscripten)pks_0.6-1.tgz(r-4.3-emscripten)
pks.pdf |pks.html✨
pks/json (API)
# Install 'pks' in R: |
install.packages('pks', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- DoignonFalmagne7 - Artificial Responses from Doignon and Falmagne
- chess - Responses to Chess Problems and Knowledge Structures
- density97 - Responses and Knowledge Structures from Taagepera et al.
- endm - Responses and Knowledge Structures from Heller and Wickelmaier
- fraction17 - Arithmetic Problems for Elementary and Middle School Students
- matter97 - Responses and Knowledge Structures from Taagepera et al.
- probability - Problems in Elementary Probability Theory
- subtraction13 - Arithmetic Problems for Elementary and Middle School Students
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 months agofrom:da6c518417. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 16 2024 |
R-4.5-linux | OK | Nov 16 2024 |
Exports:as.binmatas.patternblimblimitblimMDdelineategetKFringegetSlmPKis.backward.gradedis.downgradableis.forward.gradedis.subsetitajacobianslm
Dependencies:sets