MExPosition (version 2.0.3)

mpSTATIS.preprocess: mpSTATIS.preprocess: Preprocessing for STATIS

Description

Combines all preprocessing choices, and prepares the data for STAITS processing.

Usage

mpSTATIS.preprocess(data, column.design = NULL, row.design = NULL,  row.preprocess = 'None', column.preprocess = 'None', table.preprocess = 'None',  make.columndesign.nominal = TRUE, make.rowdesign.nominal = TRUE)

Arguments

data

Data Matrix

column.design

Matrix which identifies the tables.

row.design

Matrix which identifies the groups

row.preprocess

String option for row preprocessing with the following options: 'None' (default), 'Profile', 'Hellinger', 'Center' and 'Center_Hellinger'

column.preprocess

String option for column preprocessing with the following options: 'None' (default), 'Center', '1Norm', 'Center_1Norm' and 'Z_Score'

table.preprocess

String option for table preprocessing with the following options: 'None' (default), 'Num_Columns', 'Tucker', 'Sum_PCA', 'RV_Normalization' and 'MFA_Normalization'

make.columndesign.nominal

a boolean. If TRUE (default), table is a vector that indicates groups (and will be dummy-coded). If FALSE, table is a dummy-coded matrix.

make.rowdesign.nominal

a boolean. If TRUE (default), table is a vector that indicates groups (and will be dummy-coded). If FALSE, table is a dummy-coded matrix.

Value

data.preprocessed

Matrix of the Preprocessed Data

num.obs

Number of Observations

col.groups

Original matrix which was selected in the initial step

groupMatrix

Matrix which identifies the Tables

numgroups

Number of Tables

table.ids

Table IDs

row.preprocess

Option of row preprocessing selected

column.preprocess

Option of column preprocessing selected

table.preprocess

Option of table preprocessing selected

Details

This function calls all the preprocessing functions and consolidates the results. In addition it prepares the group matrix, and gets the data ready for processing.

References

Abdi, H., Williams, L.J., Valentin, D., & Bennani-Dosse, M. (2012). STATIS and DISTATIS: Optimum multi-table principal component analysis and three way metric multidimensional scaling. Wiley Interdisciplinary Reviews: Computational Statistics, 4, 124-167

See Also

mpSTATIS.rowPreproc, mpSTATIS.columnPreproc, mpSTATIS.tablePreproc

Examples

X <- matrix(1:10,2)
Y<- as.matrix(c('g1','g1','g1','g2','g2'))
row.preprocess='Center'
column.preprocess='Center'
table.preprocess='Sum_PCA'
preproc <-mpSTATIS.preprocess(X, column.design = t(Y), row.preprocess = row.preprocess,
 column.preprocess = column.preprocess, table.preprocess = table.preprocess)