epCA: epCA: Correspondence Analysis (CA) via ExPosition.

In ExPosition: Exploratory Analysis with the Singular Value Decomposition

Description

Correspondence Analysis (CA) via ExPosition.

Usage

epCA(DATA, DESIGN = NULL, make_design_nominal = TRUE, masses = NULL, weights = NULL,
	hellinger = FALSE, symmetric = TRUE, graphs = TRUE, k = 0)

Arguments

DATA	original data to perform a CA on.
DESIGN	a design matrix to indicate if rows belong to groups.
make_design_nominal	a boolean. If TRUE (default), DESIGN is a vector that indicates groups (and will be dummy-coded). If FALSE, DESIGN is a dummy-coded matrix.
masses	a diagonal matrix or column-vector of masses for the row items.
weights	a diagonal matrix or column-vector of weights for the column it
hellinger	a boolean. If FALSE (default), Chi-square distance will be used. If TRUE, Hellinger distance will be used.
symmetric	a boolean. If TRUE (default) symmetric factor scores for rows and columns are computed. If FALSE, the simplex (column-based) will be returned.
graphs	a boolean. If TRUE (default), graphs and plots are provided (via epGraphs)
k	number of components to return.

Details

epCA performs correspondence analysis. Essentially, a PCA for qualitative data (frequencies, proportions). If you decide to use Hellinger distance, it is best to set symmetric to FALSE.

Value

See coreCA for details on what is returned.

Author(s)

Derek Beaton

References

Abdi, H., and Williams, L.J. (2010). Principal component analysis. Wiley Interdisciplinary Reviews: Computational Statistics, 2, 433-459.
Abdi, H., and Williams, L.J. (2010). Correspondence analysis. In N.J. Salkind, D.M., Dougherty, & B. Frey (Eds.): Encyclopedia of Research Design. Thousand Oaks (CA): Sage. pp. 267-278.
Abdi, H. (2007). Singular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD). In N.J. Salkind (Ed.): Encyclopedia of Measurement and Statistics.Thousand Oaks (CA): Sage. pp. 907-912.
Greenacre, M. J. (2007). Correspondence Analysis in Practice. Chapman and Hall.

See Also

coreCA, epMCA

Examples

	data(authors)
	ca.authors.res <- epCA(authors$ca$data)

Example output

Loading required package: prettyGraphs
dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")
dev.new(): using pdf(file="Rplots3.pdf")

ExPosition documentation built on May 1, 2019, 7:06 p.m.