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MVar (version 2.2.9)

Multivariate Analysis

Description

Multivariate analysis, having functions that perform simple correspondence analysis (CA) and multiple correspondence analysis (MCA), principal components analysis (PCA), canonical correlation analysis (CCA), factorial analysis (FA), multidimensional scaling (MDS), linear (LDA) and quadratic discriminant analysis (QDA), hierarchical and non-hierarchical cluster analysis, simple and multiple linear regression, multiple factor analysis (MFA) for quantitative, qualitative, frequency (MFACT) and mixed data, biplot, scatter plot, projection pursuit (PP), grant tour method and other useful functions for the multivariate analysis.

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Version

Install

install.packages('MVar')

Monthly Downloads

562

Version

2.2.9

License

GPL-3

Maintainer

Paulo Cesar Ossani

Last Published

May 7th, 2026

Functions in MVar (2.2.9)

LocLab

Function for better position of the labels in the graphs.
Plot.CA

Graphs of the simple (CA) and multiple correspondence analysis (MCA).
Plot.FA

Graphs of the Factorial Analysis (FA).
Plot.Cor

Plot of correlations between variables.
NormData

Normalizes the data.
PP_Optimizer

Optimization function of the Projection Pursuit index (PP).
NormTest

Test of normality of the data.
PP_Index

Function to find the Projection Pursuit indexes (PP).
PCA

Principal Components Analysis (PCA).
Plot.CCA

Graphs of the Canonical Correlation Analysis (CCA).
Plot.PCA

Graphs of the Principal Components Analysis (PCA).
Plot.MFA

Graphics of the Multiple Factor Analysis (MFA).
Regr

Linear regression.
Plot.Regr

Graphs of the linear regression results.
Scatter

Scatter plot.
Plot.PP

Graphics of the Projection Pursuit (PP).
CoefVar

Coefficient of variation of the data.
DataQuan

Quantitative data set
DataFreq

Frequency data set.
DataMix

Mixed data set.
DataInd

Frequency data set.
Biplot

Biplot graph.
DataCoffee

Frequency data set.
IM

Indicator matrix.
CCA

Canonical Correlation Analysis(CCA).
CA

Correspondence Analysis (CA).
DA

Linear (LDA) and quadratic discriminant analysis (QDA).
MFA

Multiple Factor Analysis (MFA).
DataQuali

Qualitative data set
MVar-package

Multivariate Analysis.
MDS

Multidimensional Scaling (MDS).
GrandTour

Animation technique Grand Tour.
FA

Factor Analysis (FA).
Cluster

Cluster Analysis.
GSVD

Generalized Singular Value Decomposition (GSVD).