nosof88protoalcove {catlearn}

Simulation of CIRP nosof88 with proto-ALCOVE model

Description

Runs a simulation of the nosof88 CIRP using the slpALCOVE model implementation as a prototype model and nosof88train as the input representation.

Usage

  nosof88protoalcove(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 nosof88protoalcove_opt

Details

An prototype-based simulation using slpALCOVE and nosof88train. There is one radial-basis unit for each category, representing the prototype. These prototypes are calculated by taking the mean of the co-ordinates of the stimuli in a category, with the stimulus co-ordinates coming from the multdimensional scaling solution reported by Nosofsky (1987). The calculations of the means are weighted by the instantiation frequency of the stimuli. Hence, the prototypes for each condition of the experiment are different.

Other parameters of slpALCOVE are set as follows: r = 2, q = 1, initial alpha = 1 / (number of input 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 nosof88protoalcove function, and hence can not be changed without re-writing the function.

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

Value

A matrix of predicted response probabilities, in the same order and format as the observed data contained in nosof88.

Author(s)

Andy Wills & Garret O'Connell

References

Nosofsky, R.M. (1987). Attention and learning processes in the identification and categorization of integral stimuli, Journal of Experimental Psychology: Learning, Memory and Cognition, 13, 87-108.

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

See Also

nosof88, nosof88oat, nosof88train, slpALCOVE