Regularised maximum likelihood linear discriminant analysis | R Documentation |

Regularised maximum likelihood linear discriminant analysis.

```
reg.mle.lda(xnew, x, ina, lambda)
```

`xnew` |
A numerical vector or a matrix with the new observations, continuous data. |

`x` |
A matrix with numerical data. |

`ina` |
A numerical vector or factor with consecutive numbers indicating the group to which each observation belongs to. |

`lambda` |
A vector of regularization values |

Regularised maximum likelihood linear discriminant analysis is performed. The function is not extremely fast, yet is pretty fast.

A matrix with the predicted group of each observation in "xnew".
Every column corresponds to a `\lambda`

value. If you have just on value of `\lambda`

, then
you will have one column only.

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

` regmlelda.cv mle.lda, fisher.da, big.knn, weibull.nb `

```
x <- as.matrix(iris[, 1:4])
ina <- iris[, 5]
a <- reg.mle.lda(x, x, ina, lambda = seq(0, 1, by = 0.1) )
```

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