Package: MVar 2.3.0

Paulo Cesar Ossani

MVar: Multivariate Analysis

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.

Authors:Paulo Cesar Ossani [aut, cre], Marcelo Angelo Cirillo [aut]

MVar_2.3.0.tar.gz
MVar_2.3.0.tar.gz(r-4.7-arm64)MVar_2.3.0.tar.gz(r-4.7-x86_64)MVar_2.3.0.tar.gz(r-4.6-arm64)MVar_2.3.0.tar.gz(r-4.6-x86_64)
MVar_2.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MVar/json (API)

# Install 'MVar' in R:
install.packages('MVar', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.97 score 31 scripts 408 downloads 30 exports 1 dependencies

Last updated from:d09daa7c59. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK148
linux-devel-x86_64OK167
source / vignettesOK186
linux-release-arm64OK159
linux-release-x86_64OK112
wasm-releaseOK117

Exports:BiplotCACCACIClusterCoefVarDAFAGrandTourGSVDIMLocLabMDSMFANormDataNormTestPCAPlot.CAPlot.CCAPlot.CIPlot.CorPlot.FAPlot.MFAPlot.PCAPlot.PPPlot.RegrPP_IndexPP_OptimizerRegrScatter

Dependencies:MASS

Readme and manuals

Help Manual

Help pageTopics
Multivariate Analysis.MVar-package
Biplot graph.Biplot
Correspondence Analysis (CA).CA
Canonical Correlation Analysis(CCA).CCA
Confidence Intervals: Univariate and Multivariate.CI
Cluster Analysis.Cluster
Coefficient of variation of the data.CoefVar
Linear (LDA) and quadratic discriminant analysis (QDA).DA
Frequency data set.DataCoffee
Frequency data set.DataFreq
Frequency data set.DataInd
Mixed data set.DataMix
Qualitative data setDataQuali
Quantitative data setDataQuan
Factor Analysis (FA).FA
Animation technique Grand Tour.GrandTour
Generalized Singular Value Decomposition (GSVD).GSVD
Indicator matrix.IM
Function for better position of the labels in the graphs.LocLab
Multidimensional Scaling (MDS).MDS
Multiple Factor Analysis (MFA).MFA
Normalizes the data.NormData
Test of normality of the data.NormTest
Principal Components Analysis (PCA).PCA
Graphs of the simple (CA) and multiple correspondence analysis (MCA).Plot.CA
Graphs of the Canonical Correlation Analysis (CCA).Plot.CCA
Graph of Univariate and Multivariate Confidence Intervals.Plot.CI
Plot of correlations between variables.Plot.Cor
Graphs of the Factorial Analysis (FA).Plot.FA
Graphics of the Multiple Factor Analysis (MFA).Plot.MFA
Graphs of the Principal Components Analysis (PCA).Plot.PCA
Graphics of the Projection Pursuit (PP).Plot.PP
Graphs of the linear regression results.Plot.Regr
Function to find the Projection Pursuit indexes (PP).PP_Index
Optimization function of the Projection Pursuit index (PP).PP_Optimizer
Linear regression.Regr
Scatter plot.Scatter