kmsimulate | R Documentation |
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).
kmsimulate(x, n, beta, eta)
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 |
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.
Binary matrix representing the simulated data set
Doignon, J.-P. & Falmagne, J.-C. (1999). Knowledge Spaces. Springer–Verlag, Berlin.
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)
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