kmsimulate: Simulate a set of response patterns according to the BLIM

In kstMatrix: Basic Functions in Knowledge Space Theory Using Matrix Representation

Simulate a set of response patterns according to the BLIM

Description

kmsimulate returns a data set of n simulated response patterns based on the knowledge structure x given as a binary matrix. The simulation follows the BLIM (Basic Local Independence Model; see Doigon & Falmagne, 1999).

Usage

kmsimulate(x, n, beta, eta)

Arguments

x	Binary matrix representing a knowledge space
n	Number of simulated response patterns
beta	Careless error probability value or vector
eta	Lucky guess probability value or vector

Details

The beta and eta parameters must be either single numericals or vectors with a length identical to the number of rows in the x matrix. A mixture is possible.

The 'sample' function used by 'kmsimulate' might work inaccurately for knowledge structures 'x' with 2^31 or more states.

Value

Binary matrix representing the simulated data set

References

Doignon, J.-P. & Falmagne, J.-C. (1999). Knowledge Spaces. Springer–Verlag, Berlin.

Examples

kmsimulate(xpl$space, 50, 0.2, 0.1)
kmsimulate(xpl$space, 50, c(0.2, 0.25, 0.15, 0.2), c(0.1, 0.15, 0.05, 0.1))
kmsimulate(xpl$space, 50, c(0.2, 0.25, 0.15, 0.2), 0)

kstMatrix documentation built on Oct. 4, 2024, 1:08 a.m.