grt-package: General Recognition Theory

Description Details Author(s) References

Description

Functions to generate and analyze data for psychology experiments based on the General Recognition Theory.

Details

This package is written based mostly on the GRT Toolbox for MATLAB by Alfonso-Reese (2006), although many functions have been renamed and modified from the original in order to make them more general and “R-like.”

The functions grtrnorm and grtMeans are used for design categorization experiments and generating stimuli. The functions glc, gcjc, gqc, and grg are used for fitting the general linear classifier, the general conjunctive classifier, the general quadratic classifier, and the general random guessing model, respectively. The glc, gcjc, and gqc have plot methods (plot.glc, plot.gcjc, plot.gqc, plot3d.glc, plot3d.gqc).

For a complete list of functions, use library(help = "catlearn").

Author(s)

Kazunaga Matsuki

Maintainer: Andy Wills andy@willslab.co.uk

References

Alfonso-Reese, L. A. (2006) General recognition theory of categorization: A MATLAB toolbox. Behavior Research Methods, 38, 579-583.

Ashby, F. G., & Gott, R. E. (1988). Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology: Learning, Memory, & Cognition, 14, 33-53.

Ashby, F. G. (1992) Multidimensional models of perception and cognition. Lawrence Erlbaum Associates.


matsukik/grt documentation built on May 21, 2019, 12:57 p.m.