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.
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.
signature(object = "Lda")
: prints the results
signature(object = "Lda")
: prints summary information
Valentin Todorov valentin.todorov@chello.at
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")
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.