Implements instrumental variable estimators for 2^K factorial experiments with noncompliance.

Perform Maximum Likelihood Factor analysis on a covariance matrix or data matrix.

Some functions of 'ade4' and 'stats' are combined in order to obtain 
             a partition of the rows of a data table, with columns representing 
             variables of scales: quantitative, qualitative or frequency. 
             First, a principal axes method is performed and then, a combination 
             of Ward agglomerative hierarchical classification and K-means is 
             performed, using some of the first coordinates obtained from the 
             previous principal axes method. 
             In order to permit different weights of the elements to be clustered, 
             the function 'kmeansW', programmed in C++, is included. 
             It is a modification of 'kmeans'. Some graphical functions include 
             the option: 'gg=FALSE'.  When 'gg=TRUE', they  use the 'ggplot2' 
             and 'ggrepel' packages to avoid  the super-position of the labels.

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.

Brings a set of tools to help and automatically realise the description of principal component analyses (from 'FactoMineR' functions). Detection of existing outliers, identification of the informative components, graphical views and dimensions description are performed threw dedicated functions. The Investigate() function performs all these functions in one, and returns the result as a report document (Word, PDF or HTML).