Description Usage Arguments Details Value Author(s) References Examples

Predicted classification based on ‘glc’ model object.

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`object` |
object of class |

`newdata` |
a vector or a matrix containing new samples with which the classification prediction is to be made. |

`seed` |
numeric. The ‘seed’ used for the random number generator. |

`...` |
further arguments (currently unused). |

The function predict (or ‘simulate’) classification response of an observer whose noise and linear decision bounds are specified in `object`

.

The predicted category labels are matched with those used for the fit in `object`

.

If `newdata`

is missing, the predictions are made on the data used for the fit.

a vector of labels of categories to which each sample in `newdata`

is predicted to belong, according to the model in `object`

.

Author of the original Matlab routines: Leola Alfonso-Reese

Author of R adaptation: Kazunaga Matsuki

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

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