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kstMatrix (version 2.2-1)

Basic Functions in Knowledge Space Theory Using Matrix Representation

Description

Knowledge space theory by Doignon and Falmagne (1999) is a set- and order-theoretical framework, which proposes mathematical formalisms to operationalize knowledge structures in a particular domain. The 'kstMatrix' package provides basic functionalities to generate, handle, and manipulate knowledge structures and knowledge spaces. Opposed to the 'kst' package, 'kstMatrix' uses matrix representations for knowledge structures. Furthermore, 'kstMatrix' contains several knowledge spaces developed by the research group around Cornelia Dowling through querying experts.

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Version

Install

install.packages('kstMatrix')

Monthly Downloads

12,102

Version

2.2-1

License

GPL-3

Maintainer

Cord Hockemeyer

Last Published

January 23rd, 2026

Functions in kstMatrix (2.2-1)

Compute the fringe of a state within a knowledge structure using its basis

Reduce a family of knowledge states with respect to item equivalence

Plot a Hasse diagram

kmneighbourhood

Compute the neighbourhod of a state within a knowledge structure

kmnneighbourhood

Compute the n-neighbourhod of a state within a knowledge structure

Knowledge spaces on reading and writing abilities

kmsurmisefunction

Compute the surmise function for a knowledge space or basis

Convert a binary matrix to a kmfamset object (family of sets)

Convert a binary matrix to a kmstructure object

Create trivial knowledge spaces

Simulate a set of response patterns according to the BLIM

Knowledge space on linear functions

Generate a knowledge structure from a set of response patterns

Convert a binary matrix to a kmspace object

Validate a knowledge structure against a data set

Compute the fringe of a state within a knowledge structure

Close a family of sets under union

Check for wellgradedness of a knowledge structure

kmlearningpaths

Determine all learning paths in a knowledge structure

Small example knowledge space

Determine the notions of a knowledge structure

Convert an IITA result into a surmise relation matrix

kmsurmiserelation

Compute the surmise relation of a quasi-ordinal knowledge space

Determine all gradations between two states

Compute the symmetric set difference between two sets

Test if a state is contained in a family of states

Knowledge spaces on AutoCAD knowledge

Validate a surmise relation against a data set

Perform a probabilistic knowledge assessment

kmassessmentsimulation

Simulate assessments for a set of response patterns

kmassessbayesian

Update probability distribution applying Bayesian update

Derive a basis from a surmise function

kmassesshalfsplit

Determine next question for probabilistic knowledge assessment

Determine the basis of a knowledge space from a surmise relation

kmassessinformative

Determine next question for probabilistic knowledge assessment

kmassessmultiplicative

Update probability distribution applying multiplicative rule

Generic kmbasis() function

Test two double numbers on equity with a certain tolerance

Determine a color vector based on probabilities

kmbasisneighbourhood

Compute the neighbourhod of a state within a knowledge structure using its basis

kmbasis.kmsurmisefunction

Determine the basis for a surmise function

kmbasis.kmsurmiserelation

Determine the basis of a knowledge space from a surmise relation

Compute the distance between a data set and a knowledge structure

Compute the basis of a knowledge space

Knowledge spaces on fractions