Description Objects from the Class Slots Extends Methods Author(s) References See Also Examples

Robust linear discriminant analysis is performed by replacing the classical group means and withing group covariance matrix by robust equivalents based on MCD.

Objects can be created by calls of the form `new("Linda", ...)`

but the
usual way of creating `Linda`

objects is a call to the function
`Linda`

which serves as a constructor.

`call`

:The (matched) function call.

`prior`

:Prior probabilities used, default to group proportions

`counts`

:number of observations in each class

`center`

:the group means

`cov`

:the common covariance matrix

`ldf`

:a matrix containing the linear discriminant functions

`ldfconst`

:a vector containing the constants of each linear discriminant function

`method`

:a character string giving the estimation method used

`X`

:the training data set (same as the input parameter x of the constructor function)

`grp`

:grouping variable: a factor specifying the class for each observation.

`l1med`

:wheather L1 median was used to compute group means.

Class `"LdaRobust"`

, directly.
Class `"Lda"`

, by class "LdaRobust", distance 2.

No methods defined with class "Linda" in the signature.

Valentin Todorov [email protected]

Todorov V & Filzmoser P (2009),
An Object Oriented Framework for Robust Multivariate Analysis.
*Journal of Statistical Software*, **32**(3), 1–47.
URL http://www.jstatsoft.org/v32/i03/.

`LdaRobust-class`

, `Lda-class`

, `LdaClassic`

, `LdaClassic-class`

1 | ```
showClass("Linda")
``` |

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