R: General Recognition Theory

# General Recognition Theory

## Documentation for package ‘grt’ version 0.2.1

- DESCRIPTION file
- Package README

## Help Pages

grt-package | General Recognition Theory
angle2cart | Convert 'new' to 'old' glcStruct format
cart2angle | Convert 'old' to 'new' glcStruct format
coef.gcjc | Extract 'glc' or 'gcjc' coefficients
coef.glc | Extract 'glc' or 'gcjc' coefficients
coef.glcStruct | Extract 'glc' or 'gcjc' coefficients
dprime | Calculate d' (d-prime)
dprimef | Calculate d' (d-prime)
extractAIC.gcjc | extractAIC method for class 'glc', 'gqc', 'gcjc', and 'grg'
extractAIC.glc | extractAIC method for class 'glc', 'gqc', 'gcjc', and 'grg'
extractAIC.gqc | extractAIC method for class 'glc', 'gqc', 'gcjc', and 'grg'
extractAIC.grg | 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
grt | General Recognition Theory
grtMeans | Obtain means of two multivariate normal populations satisfying certain criteria
grtrnorm | Sample from multiple multivariate normal distributions
ldb | Linear Decision Bound
ldb.p.correct | Probability of correct classification based on the optimal linear decision bound.
lines.gqcStruct | lines Method for class 'gqc'
logLik.gcjc | Log-Likelihood of a 'glc' or 'gcjc' Object
logLik.gcjcStruct | Log-Likelihood of a 'glcStruct' or 'gcjcStruct' Object
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
mcovs.default | Calculate sample means and covariance(s) of multivariate data
mcovs.formula | 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
plot.gcjc | Plot Method for Class 'gcjc'
plot.glc | Plot Method for Class 'glc'
plot.gqc | plot Method for Class 'gqc'
plot3d.glc | plot3d Method for Class 'glc'
plot3d.gqc | plot3d Method for Class 'gqc'
predict.glc | predict method for General Linear Classifier
print.gcjc | General Conjunctive Classifier
print.glc | General Linear Classifier
print.gqc | General Quadratic Classifier
qdb | Quadratic Decision Bound
qdb.p.correct | the proportion correct of the quadratic decision boundary.
scale | Scale method for the class 'glc' and 'gqc'
scale.glc | Scale method for the class 'glc' and 'gqc'
scale.gqc | Scale method for the class 'glc' and 'gqc'
subjdemo_1d | Sample dataset of a categorization experiment with 1D stimuli.
subjdemo_2d | Sample dataset of a categorization experiment with 2D stimuli.
subjdemo_3d | Sample dataset of a categorization experiment with 3D stimuli.
subjdemo_cj | Sample dataset of a categorization experiment with 2D conjunctive stimuli.
unscale | Un-scale or re-center the scaled or centered Matrix-like object