Calculate the proportion correct obtained by categorizing samples form one multivariate normal population using the quadratic decision boundary.

1 | ```
qdb.p.correct(x, qdb, refpts = colMeans(x))
``` |

`x` |
a vector or matrix containing the values of samples from one multivariate normal population. |

`qdb` |
object of class |

`refpts` |
a numeric vector used as a reference point to determine the correct side of the |

The function assumes that all the points specified in `x`

belong to just one category.

Author of the original Matlab routine â€˜quadbndpercorrâ€™: 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.

1 2 3 4 5 | ```
data(subjdemo_2d)
tmp <- split(subjdemo_2d, subjdemo_2d$category)
mc <- mcovs(category ~ x + y, data=subjdemo_2d, pooled=FALSE)
db <- qdb(mc$means, mc$covs)
qdb.p.correct(tmp[[1]][,2:3], db)
``` |

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