RSDA (version 1.1)

cfa.CVPRealz: Compute the eigenvectors

Description

Compute the eigenvectors to the matrix of column profiles.

Usage

cfa.CVPRealz(sym.data, TFilas, TColumnas, TT, z)

Arguments

sym.data

Should be a symbolic data table read with the function read.sym.table(...).

TFilas

Value of the total sum of the rows of the matrix.

TColumnas

Value of the total sum of the columns of the matrix.

TT

Value of the total sum of the matrix.

z

Eigenvectors of the correlation matrix.

Value

• Return the eigenvectors.

References

Rodriguez, O. (2011). Correspondence Analysis for Symbolic Multivalued Variables. Workshop in Symbolic Data Analysis Namur, Belgium.

See Also

sym.cfa

Examples

data(ex_cfa1) 
res<-cfa.totals(ex_cfa1)
Z<-cfa.MatrixZ(ex_cfa1,res$TotalRows,res$TotalColumns) 
svd<-eigen(Z)
MVPRealz<-cfa.CVPRealz(ex_cfa1,res$TotalRows,res$TotalColumns,res$Total,svd$vectors)
Mzz<-cfa.Czz(ex_cfa1,res$TotalRows,res$TotalColumns,MVPRealz,svd$values)
CMM<-cfa.minmax(ex_cfa1,res$TotalRows,res$TotalRowsMin,res$TotalRowsMax,
            res$TotalColumns,res$TotalColumnsMin,res$TotalColumnsMax,
            res$Total,MVPRealz,Mzz)