CA_English: Correspondence Analysis (CA).

In MVar: Multivariate Analysis

Correspondence Analysis (CA).

Description

Performs simple correspondence analysis (CA) and multiple (MCA) in a data set.

Usage

CA(data, typdata = "f", typmatrix = "I")

Arguments

data	Data to be analyzed (contingency table).
typdata	"f" for frequency data (default), "c" for qualitative data.
typmatrix	Matrix used for calculations when typdata = "c". "I" for indicator matrix (default), "B" for Burt's matrix.

Value

depdata	Verify if the rows and columns are dependent, or independent by the chi-square test, at the 5% significance level.
typdata	Data type: "F" frequency or "C" qualitative.
numcood	Number of principal components.
mtxP	Matrix of the relative frequency.
vtrR	Vector with sums of the rows.
vtrC	Vector with sums of the columns.
mtxPR	Matrix with profile of the rows.
mtxPC	Matrix with profile of the columns
mtxZ	Matrix Z.
mtxU	Matrix with the eigenvectors U.
mtxV	Matrix with the eigenvectors V.
mtxL	Matrix with eigenvalues.
mtxX	Matrix with the principal coordinates of the rows.
mtxY	Matrix with the principal coordinates of the columns.
mtxAutvlr	Matrix of the inertias (variances), with the proportions and proportions accumulated.

Author(s)

Paulo Cesar Ossani

Marcelo Angelo Cirillo

References

MINGOTI, S. A. Analise de dados atraves de metodos de estatistica multivariada: uma abordagem aplicada. Belo Horizonte: UFMG, 2005. 297 p.

RENCHER, A. C. Methods of multivariate analysis. 2th. ed. New York: J.Wiley, 2002. 708 p.

See Also

Plot.CA

Examples

data(DataFreq) # frequency data set

data <- DataFreq[,2:ncol(DataFreq)]

rownames(data) <- as.character(t(DataFreq[1:nrow(DataFreq),1]))

res <- CA(data = data, "f") # performs CA

print("Is there dependency between rows and columns?"); res$depdata

print("Number of principal coordinates:"); res$numcood

print("Principal coordinates of the rows:"); round(res$mtxX,2)

print("Principal coordinates of the columns:"); round(res$mtxY,2)

print("Inertia of the principal components:"); round(res$mtxAutvlr,2)

MVar documentation built on Aug. 19, 2023, 5:12 p.m.