The class LdaPP
represents an algorithm for robust linear discriminant
analysis by projection-pursuit approach. The objects of class LdaPP
contain the results
of the robust linear discriminant analysis by projection-pursuit approach.
Objects can be created by calls of the form new("LdaPP", ...)
but the
usual way of creating LdaPP
objects is a call to the function
LdaPP
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
raw.ldf
:a matrix containing the raw linear discriminant functions - see Details in LdaPP
raw.ldfconst
:a vector containing the raw constants of each raw linear discriminant function - see Details in LdaPP
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.
Class "LdaRobust"
, directly.
Class "Lda"
, by class "LdaRobust", distance 2.
signature(object = "LdaPP")
: 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. If the argument raw=TRUE
is set the raw
(obtained by the first approximation algorithm) linear discriminant
function and constant will be used.
Valentin Todorov valentin.todorov@chello.at and Ana Pires apires@math.ist.utl.pt
Pires, A. M. and A. Branco, J. (2010) Projection-pursuit approach to robust linear discriminant analysis Journal Multivariate Analysis, Academic Press, Inc., 101, 2464--2485.
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").
LdaRobust-class
, Lda-class
,
LdaClassic
, LdaClassic-class
,
Linda
, Linda-class