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

The class `Lda`

serves as a base class for deriving
all other classes representing the results of classical
and robust Linear Discriminant Analisys methods

A virtual Class: No objects may be created from it.

`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.

- predict
`signature(object = "Lda")`

: calculates prediction using the results in`object`

. An optional data frame or matrix in which to look for variables with which to predict. If omitted, the training data set is used. If the original fit used a formula or a data frame or a matrix with column names, newdata must contain columns with the same names. Otherwise it must contain the same number of columns, to be used in the same order.- show
`signature(object = "Lda")`

: prints the results- summary
`signature(object = "Lda")`

: prints summary information

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/.

`LdaClassic`

, `LdaClassic-class`

, `LdaRobust-class`

1 | ```
showClass("Lda")
``` |

rrcov documentation built on May 30, 2017, 3:23 a.m.

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