kmdist

<code>kmdist</code> returns a named vector with the frequencies of distances
between a set of response patterns and a knowledge structure. This vector
can be used to compute, e.g., the Discrepancy Index (DI) or the
Distance Agreement Coefficient (DA).

Knowledge space theory by Doignon and Falmagne (1999)
<doi:10.1007/978-3-642-58625-5> 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.

Cord Hockemeyer

kstMatrix

Basic Functions in Knowledge Space Theory Using Matrix
Representation

Peter Steiner

Wai Wong

kmdist function

<dl><dt>data</dt>
<dd>Binary matrix representing a set of response patterns</dd>
<dt>struct</dt>
<dd>Binary matrix representing a knowledge structure</dd></dl>

Arguments

Compute the distance between a data set and a knowledge structure — kmdist

<dl>

<dt>data</dt>
<dd>Binary matrix representing a set of response patterns</dd>


<dt>struct</dt>
<dd>Binary matrix representing a knowledge structure</dd>

</dl>

kmdist: Compute the distance between a data set and a knowledge structure

Description

Usage

Value

Arguments

See Also

Examples