grt: General Recognition Theory

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

AuthorKazunaga Matsuki
Date of publication2014-04-10 15:20:06
MaintainerKazunaga Matsuki <>
LicenseGPL (>= 2)

View on CRAN

Man pages

coef.glc: Extract 'glc' or 'gcjc' coefficients

dprime: Calculate d' (d-prime)

extractAIC.glc: extractAIC method for class 'glc', 'gqc', 'gcjc', and 'grg'

gaborPatch: Draw a gray-scale Gabor Patch

gcjc: General Conjunctive Classifier

gcjcStruct: General Conjunctive Classifier structure

glc: General Linear Classifier

glcStruct: General Linear Classifier structure

gqc: General Quadratic Classifier

gqcStruct: General Quadratic Classifier structure.

grg: General Random Guessing model

grtMeans: Obtain means of two multivariate normal populations...

grt-package: General Recognition Theory

grtrnorm: Sample from multiple multivariate normal distributions

ldb: Linear Decision Bound

ldb.p.correct: Probability of correct classification based on the optimal...

lines.gqcStruct: lines Method for class 'gqc'

logLik.glc: Log-Likelihood of a 'glc' or 'gcjc' Object

logLik.glcStruct: Log-Likelihood of a 'glcStruct' or 'gcjcStruct' Object

logLik.gqc: Log-Likelihood of a 'gqc' Object

logLik.gqcStruct: Log-Likelihood of a 'gqcStruct' Object

mcovs: Calculate sample means and covariance(s) of multivariate data

new2old_par: Convert 'new' to 'old' glcStruct format

old2new_par: Convert 'old' to 'new' glcStruct format

plot3d.glc: plot3d Method for Class 'glc'

plot3d.gqc: plot3d Method for Class 'gqc'

plot.gcjc: Plot Method for Class 'gcjc'

plot.glc: Plot Method for Class 'glc'

plot.gqc: plot Method for Class 'gqc'

predict.glc: predict method for General Linear Classifier

qdb: Quadratic Decision Bound

qdb.p.correct: the proportion correct of the quadratic decision boundary.

scale.glc: Scale method for the class 'glc' and 'gqc'

subjdemo_1d: Sample dataset of a categorization experiment with 1D...

subjdemo_2d: Sample dataset of a categorization experiment with 2D...

subjdemo_3d: Sample dataset of a categorization experiment with 3D...

subjdemo_cj: Sample dataset of a categorization experiment with 2D...

unscale: Un-scale or re-center the scaled or centered Matrix-like...

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