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.
covobj
:object of class "Cov"
containing the estimate
of the common covariance matrix of the centered data. It is not NULL
only in case of method "B".
control
:object of class "CovControl"
specifying which estimate
and with what estimation options to use for the group means and common covariance
(or NULL
for classical linear discriminant analysis)
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. tools:::Rd_expr_doi("10.18637/jss.v032.i03").
LdaClassic
, LdaClassic-class
, LdaRobust-class