ExPosition: Ex ploratory Analysis with the Singular Value DecomPosition
coreMDS
Small data set on flavor perception and preferences for coffee.
calculateConstraints
Chi-square Distance computation
Some of authors' personal beer tasting notes.
computeMW
Ten assessors sort eight beers into groups.
(A truncated form of) Punctuation used by six authors (data).
Correspondence analysis preprocessing
epCA: Correspondence Analysis (CA) via ExPosition.
epGPCA: Generalized Principal Components Analysis (GPCA) via ExPosition.
corePCA
createDefaultDesign
caSupplementalElementsPreProcessing
Correspondence Analysis preprocessing.
Twelve wines from 3 regions in France with 18 attributes.
Data of categories of images as view in an f MRI experiment.
epGraphs: ExPosition plotting function
epMCA: Multiple Correspondence Analysis (MCA) via ExPosition.
epMDS: Multidimensional Scaling (MDS) via ExPosition.
Makes distances and weights for MDS analyses (see epMDS
). makeNominalData
How twelve French families spend their income on groceries.
Print results from the singular value decomposition (SVD) in ExPosition
genPDQ: the GSVD
epPCA: Principal Component Analysis (PCA) via ExPosition.
Print results from ExPosition
Preprocessing for CA-based analyses
Checks if data are disjunctive.
Small data set for Partial Least Squares-Correspondence Analysis
Six wines described by several assessors with rank attributes.
Twelve wines from 3 regions in France with 16 attributes.
pause
designCheck
hellingerSupplementaryRowsPreProcessing
Preprocessing for supplementary rows in Hellinger analyses.
Supplemental projections.
Fisher's iris Set (for ExPosition)
Data from 17 Alzheimer's Patient-Spouse dyads.
Alzheimer's Patient-Spouse Dyads.
Pick which generalized SVD (or related) decomposition to use.
pcaSupplementaryRowsPreProcessing
Preprocessing for supplemental rows in PCA.
pcaSupplementaryColsPreProcessing
Preprocessing for supplementary columns in PCA.
Print Correspondence Analysis (CA) results
Hellinger version of CA preprocessing
Print epGraphs results
Normalize the rows of a matrix.
Print Generalized Principal Components Analysis (GPCA) results
hellingerSupplementaryColsPreProcessing
Preprocessing for supplementary columns in Hellinger analyses.
Perform Rv coefficient computation.
Scaling functions for ExPosition.
mdsSupplementalElementsPreProcessing
MDS preprocessing
Print Multiple Correspondence Analysis (MCA) results
Supplementary columns
Supplementary rows
Transform data for MDS analysis.
Faces analyzed using Four Algorithms
A collection of beer tasting notes from untrained assessors.
Twenty words described by 2 features.
A collection of beer tasting notes from untrained assessors.
mca.eigen.fix
Six wines described by several assessors with qualitative attributes.
Print Multidimensional Scaling (MDS) results
Print Principal Components Analysis (PCA) results
Six wines described by 3 assessors.
Wines Data from 12 assessors described by 15 flavor profiles.
coreCA
acknowledgements