nosof94bnalcove: Simulation of CIRP nosof94 with BN-ALCOVE model

View source: R/nosof94bnalcove.R

nosof94bnalcoveR Documentation

Simulation of CIRP nosof94 with BN-ALCOVE model


Runs a simulation of the nosof94 CIRP using the slpALCOVE model implementation as an exemplar model and nosof94train as the input representation. This simulation replicates the one reported by Nosofsky et al. (1994).


  nosof94bnalcove(params = c(6.33,0.011,0.409,0.179))



A vector containing values for c, phi, la, and lw, in that order. See slpALCOVE for an explanation of these parameters.


An exemplar-based simulation using slpALCOVE and nosof94train. The co-ordinates for the radial-basis units are assumed, and use the same binary representation as the abstract category structure.

The defaults for params are the best fit of the model to the nosof94 CIRP. The derivation of this fit is described by Nosofsky et al. (1994).

The other parameters of slpALCOVE are set as follows: r = 1, q = 1, initial alpha = 1 / number of dimensions, initial w = 0. These values are conventions of modeling with ALCOVE, and should not be considered as free parameters. They are set within the nosof88bnalcove function, and hence can't be changed without re-writing the function.

This is a replication of the simulation reported by Nosofsky et al. (1994). Compared to other published simulations with the ALCOVE model, their simulation is non-standard in a number of respects:

1. A background noise ('BN') decision rule is used (other simulations use an exponential ratio rule).

2. As a consequence of #1, absence of a category label is represented by a zero (other simulations use -1).

3. The sum of the attentional weights is constrained to be 1 on every trial (other simulations do not apply this constraint).

The current simulation replicates these non-standard aspects of the Nosofsky et al. (1994) simulation.


A matrix of predicted response probabilities, in the same order and format as the observed data contained in nosof94.


Andy Wills


Nosofsky, R.M., Gluck, M.A., Plameri, T.J., McKinley, S.C. and Glauthier, P. (1994). Comparing models of rule-based classification learning: A replication and extension of Shepaard, Hovland, and Jenkins (1961). Memory and Cognition, 22, 352–369

See Also

nosof94, nosof94oat, nosof94train, slpALCOVE, nosof94bnalcove

catlearn documentation built on March 26, 2022, 1:07 a.m.