Package: pks 0.7-0

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:Florian Wickelmaier [aut, cre], Juergen Heller [aut], Julian Mollenhauer [aut], Pasquale Anselmi [ctb], Debora de Chiusole [ctb], Andrea Brancaccio [ctb], Luca Stefanutti [ctb], Paul Doerrbecker [ctb]

pks_0.7-0.tar.gz
pks_0.7-0.tar.gz(r-4.7-any)pks_0.7-0.tar.gz(r-4.6-any)
pks_0.7-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
pks/json (API)

# Install 'pks' in R:

install.packages('pks', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

angles - Responses to Geometry Problems and Knowledge Structures
chess - Responses to Chess Problems and Knowledge Structures
circles - Responses to Geometry Problems and Knowledge Structures
density97 - Responses and Knowledge Structures from Taagepera et al.
DoignonFalmagne7 - Artificial Responses from Doignon and Falmagne
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

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.28 score 2 packages 32 scripts 736 downloads 15 exports 1 dependencies

Last updated from:6a08e06f4d. Checks:4 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	109
source / vignettes	OK	197
linux-release-x86_64	OK	96
wasm-release	OK	96

Exports:as.binmat as.pattern blim blimit blimMD delineate getKFringe getSlmPK is.backward.graded is.downgradable is.forward.graded is.subset ita jacobian slm

Dependencies:sets

Parameter Estimation in Probabilistic Knowledge Structures -- Step by Step

The basic local independence model | The simple learning model

Rendered fromEstimationStepByStep.Rnwusingutils::Sweave

Last update: 2024-09-17
Started: 2023-07-07

Help page	Topics
Basic Local Independence Models (BLIMs)	anova.blim blim blimMD coef.blim deviance.blim logLik.blim nobs.blim
Basic Local Independence Model Identification Analysis	blimit
Responses to Chess Problems and Knowledge Structures	chess
Conversion between Representations of Responses or States	as.binmat as.pattern conversion is.subset
Delineate a Knowledge Structure by a Skill Function	delineate
Artificial Responses from Doignon and Falmagne (1999)	DoignonFalmagne7
Responses and Knowledge Structures from Heller and Wickelmaier (2013)	endm
Outer and Inner Fringes of a Knowledge Structure	getKFringe
Forward-/Backward-Gradedness and Downgradability of a Knowledge Structure	gradedness is.backward.graded is.downgradable is.forward.graded
Responses to Geometry Problems and Knowledge Structures	angles circles hsgeometry
Item Tree Analysis (ITA)	ita print.ita
Jacobian Matrix for Basic Local Independence Model	jacobian
Diagnostic Plot for Basic Local Independence Models	plot.blim
Predict Knowledge States from Basic Local Independence Models (BLIMs)	predict.blim predict.slm
Print a blim Object	print.blim
Problems in Elementary Probability Theory	probability
Residuals for Basic Local Independence Models	residuals.blim
Arithmetic Problems for Elementary and Middle School Students	fraction17 schoolarithm subtraction13
Simulate Responses from Basic Local Independence Models (BLIMs)	simulate.blim
Simple Learning Models (SLMs)	coef.slm getSlmPK print.slm slm
Responses and Knowledge Structures from Taagepera et al. (1997)	density97 matter97 Taagepera

Package: pks 0.7-0

pks: Probabilistic Knowledge Structures

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)