The package contains methods using stochastic approximation
to analyse (big) data (streams).
Matrix, graphics, plotrix, datasets, FactoMineR

R (>= 2.14.0), plotrix, FactoMineR, Matrix

Instrumental Variables Estimation for 2^k Factorial Experiments
c(person(given = "Matthew",
family = "Blackwell",
role = c("aut", "cre"),
email = "mblackwell@gov.harvard.edu",
comment = c(ORCID = "0000-0002-3689-9527")),
person(given = "Nicole",
family = "Pashley",
role = "aut",
email = "npashley@g.harvard.edu"))
Implements instrumental variable estimators for 2^K factorial experiments with noncompliance.
Matthew Blackwell [aut, cre] (<https://orcid.org/0000-0002-3689-9527>),
Nicole Pashley [aut]

Extract and Visualize the Results of Multivariate Data Analyses
c(
person("Alboukadel", "Kassambara", role = c("aut", "cre"), email = "alboukadel.kassambara@gmail.com"),
person("Fabian", "Mundt", role = c("aut"), email = "f.mundt@inventionate.de")
)
Provides some easy-to-use functions to extract and visualize
the output of multivariate data analyses, including 'PCA' (Principal Component
Analysis), 'CA' (Correspondence Analysis), 'MCA' (Multiple Correspondence Analysis),
'MFA' (Multiple Factor Analysis) and 'HMFA' (Hierarchical Multiple Factor Analysis)
functions from different R packages. It contains also functions for simplifying some clustering analysis steps
and provides 'ggplot2' - based elegant data visualization.
cluster, dendextend, grid, stats, reshape2, ggrepel, abind
'cluster_utilities.R' 'decathlon2.R' 'eigenvalue.R'
'utilities.R' 'dist.R' 'fviz_dend.R' 'hcut.R'
'print.factoextra.R' 'get_pca.R' 'fviz_cluster.R' 'eclust.R'
'facto_summarize.R' 'fviz_add.R' 'fviz_ca.R' 'fviz_contrib.R'
'fviz_cos2.R' 'get_hmfa.R' 'fviz_hmfa.R' 'get_mca.R'
'fviz_mca.R' 'get_mfa.R' 'fviz_mfa.R' 'fviz_nbclust.R'
'fviz_pca.R' 'fviz_silhouette.R' 'get_ca.R'
'get_clust_tendency.R' 'hkmeans.R' 'housetasks.R'
'multishapes.R' 'poison.R'
Alboukadel Kassambara [aut, cre],
Fabian Mundt [aut]

Provides some easy-to-use functions to extract and visualize the
output of multivariate data analyses, including 'PCA' (Principal Component
Analysis), 'CA' (Correspondence Analysis), 'MCA' (Multiple Correspondence
Analysis), 'FAMD' (Factor Analysis of Mixed Data), 'MFA' (Multiple Factor Analysis) and 'HMFA' (Hierarchical Multiple
Factor Analysis) functions from different R packages. It contains also functions
for simplifying some clustering analysis steps and provides 'ggplot2' - based
elegant data visualization.
abind, cluster, dendextend, FactoMineR, ggpubr, grid, stats,
reshape2, ggrepel, tidyr
'cluster_utilities.R' 'decathlon2.R' 'print.factoextra.R'
'get_hmfa.R' 'fviz_hmfa.R' 'get_mfa.R' 'fviz_mfa.R'
'deprecated.R' 'fviz_add.R' 'eigenvalue.R' 'utilities.R'
'dist.R' 'fviz_dend.R' 'hcut.R' 'get_pca.R' 'fviz_cluster.R'
'eclust.R' 'facto_summarize.R' 'fviz.R' 'fviz_ca.R'
'fviz_contrib.R' 'fviz_cos2.R' 'fviz_ellipses.R' 'fviz_famd.R'
'get_mca.R' 'fviz_mca.R' 'fviz_mclust.R' 'fviz_nbclust.R'
'fviz_pca.R' 'fviz_silhouette.R' 'get_ca.R'
'get_clust_tendency.R' 'get_famd.R' 'hkmeans.R' 'housetasks.R'
'multishapes.R' 'poison.R'