SimultAnR (version 1.1)

SimultAnR_1.1-package: Correspondence and Simultaneous Analysis

Description

This package performs classical correspondence analysis (CA) and simultaneous analysis (SA). Simultaneous analysis is a factorial methodology developed for the joint treatment of a set of several contingency tables. In SA tables having the same rows, are concatenated row-wise. In this version of the package a multiple option have been included for the simultaneous analysis of tables having the same columns, concatenated column-wise. This way, a MSA allows to perform the analysis of an indicator matrix where the rows represent individuals. In this package, functions for computation, summaries and graphical visualization in two dimensions are provided, including options to display partial and supplementary points.

Details

Package:

SimultAnR_1.1

Type:

Package

Version:

1.0

Date:

2013-07-28

License:

GPL (>=2)

LazyLoad:

yes

LazyData:

yes

The main function of the package is SimAn() which performs simultaneous analysis. The input dataset is the concatenation of the frequency/contingency tables to be jointly analyzed. The package can also be used to perform classical correspondence analysis of frequency/contingency tables by means of the function CorrAn().

References

Goitisolo, B. (2002). El Analisis Simultaneo. Propuesta y aplicacion de un nuevo metodo de analisis factorial de tablas de contingencia. Phd thesis, Basque Country University Press, Bilbao.

Zarraga, A. & Goitisolo, B. (2002). Methode factorielle pour l analyse simultanee de tableaux de contingence. Revue de Statistique Appliquee, L, 47--70

Zarraga, A. & Goitisolo, B. (2003). Etude de la structure inter-tableaux a travers l Analyse Simultanee, Revue de Statistique Appliquee, LI, 39--60.

Zarraga, A. and Goitisolo, B. (2006). Simultaneous analysis: A joint study of several contingency tables with different margins. In: M. Greenacre, J. Blasius (Eds.), Multiple Correspondence Analysis and Related Methods, Chapman & Hall/CRC, Boca Raton, Fl, 327--350.

Zarraga, A. & Goitisolo, B. (2009). Simultaneous analysis and multiple factor analysis for contingency tables: Two methods for the joint study of contingency tables. Computational Statistics and Data Analysis, 53, 3171--3182.

Zarraga, A. & Goitisolo, B. (2011). Simultaneous Analysis in S-PLUS: The SimultAn Package. Journal of Statistical Software, 70 (11), 1--22.

See Also

CorrAn, summary.CorrAn, plot.CorrAn, SimAn, summary.SimAn, plot.SimAn,

shoplifting, traffic.

Examples

######################################################################
### Package and data                                               ###
######################################################################

data(shoplifting)

######################################################################
### Correspondence Analysis                                        ###
######################################################################
dataCA <- shoplifting[, 1:9]

### CA without supplementary elements
CorrAn.out <- CorrAn(data=dataCA)

### CA with supplementary rows/columns
CorrAn.out <- CorrAn(data=dataCA, sr=13)
CorrAn.out <- CorrAn(data=dataCA, sc=9)
CorrAn.out <- CorrAn(data=dataCA, sr=13, sc=9)

### CA with supplementary columns and without output for rows
CorrAn.out <- CorrAn(data = dataCA, sc=9, oac=0, oar = 0)

### Summary
summary(CorrAn.out)

### Graphs on screen
plot(CorrAn.out, s1=1, s2=2, screen=TRUE)

### Graphs on a pdf file
pdf('CAGr.pdf', paper="a4r", width=12, height=9)
plot(CorrAn.out, s1=1, s2=2, screen=FALSE)
dev.off()

###other
args(CorrAn)
names(CorrAn.out)
CorrAn.out
CorrAn.out$totalin
CorrAn.out$Gs
             
             

######################################################################
### Simultaneous Analysis                                          ###
######################################################################

dataSA <- shoplifting

### SA without supplementary elements
SimAn.out <- SimAn(data=dataSA, G=2, acg=list(1:9,10:18), weight= 2,
   nameg=c("M", "F"))

### SA with supplementary rows/columns
SimAn.out <- SimAn(data=dataSA, G=2, acg=list(1:8,10:17), weight= 2,
   nameg=c("M", "F"), sr= 13)
SimAn.out <- SimAn(data=dataSA, G=2, acg=list(1:8,10:17), weight= 2,
   nameg=c("M", "F"), sr= 13, sc=c(9,18))
                            
## Multiple SA with supplementary rows and without output for columns)
SimAn.out <- SimAn(data = t(dataSA), G = 2, arg = list(1:9, 10:18), 
   weight = 2, nameg=c("M", "F"), sr = 11, oac=0, multiple = 1)


### Summary
summary(SimAn.out)
                                                        
### Graphs on screen
plot(SimAn.out)


### Graphs on a pdf file
pdf('SAGr.pdf', paper="a4r", width=12, height=9)
plot(SimAn.out, s1=1, s2=2, screen=FALSE)
dev.off()

###other
args(SimAn)
names(SimAn.out)
SimAn.out
SimAn.out$I
SimAn.out$resi