catlearn (version 0.8)

nosof94exalcove: Simulation of CIRP nosof94 with ex-ALCOVE model

Description

Runs a simulation of the nosof94 CIRP using the slpALCOVE model implementation as an exemplar model and nosof94train as the input representation.

Usage

nosof94exalcove(params = NULL)

Arguments

params

A vector containing values for c, phi, la, and lw, in that order, e.g. params = c(2.1, 0.6, 0.09, 0.9). See slpALCOVE for an explanation of these parameters. Where params = NULL, best-fitting parameters are derived from optimzation archive nosof94exalcove_opt

Value

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

Details

N.B.: This simulation uses a standard version of ALCOVE. For a replication of the ALCOVE simulation of these data reported by Nosofsky et al. (1994), which is non-standard in a number of respects, see nosof94bnalcove.

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.

Other parameters of slpALCOVE are set as follows: r = 1, q = 1, initial alpha = 1/3, initial w = 0. These values are conventions of modeling with ALCOVE, and should not be considered as free parameters. They are set within the nosof88exalcove function, and hence can't be changed without re-writing the function.

This simulation is reported in Wills & O'Connell (n.d.).

References

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

Wills, A.J. & O'Connell (n.d.). Averaging abstractions. Manuscript in preparation.

See Also

nosof94, nosof94oat, nosof94train, slpALCOVE, nosof94bnalcove