# statis: Structuration des Tableaux à Trois Indices de la Statistique... In multiblock: Multiblock Data Fusion in Statistics and Machine Learning

## Description

This is a wrapper for the `ade4::statis` function for computing STATIS.

## Usage

 `1` ```statis(X, ncomp = 3, scannf = FALSE, tol = 1e-07, ...) ```

## Arguments

 `X` `list` of input blocks. `ncomp` `integer` number of components to extract. `scannf` `logical` indicating if eigenvalue bar plot shoulde be displayed. `tol` `numeric` eigenvalue threshold tolerance. `...` additional arguments (not used).

## Details

STATIS is a method, related to MFA, for analysing two or more blocks. It also decomposes the data into a low-dimensional subspace but uses a different scaling of the individual blocks.

## Value

`multiblock` object including relevant scores and loadings. Relevant plotting functions: `multiblock_plots` and result functions: `multiblock_results`.

## References

Lavit, C.; Escoufier, Y.; Sabatier, R.; Traissac, P. (1994). The ACT (STATIS method). Computational Statistics & Data Analysis. 18: 97

Overviews of available methods, `multiblock`, and methods organised by main structure: `basic`, `unsupervised`, `asca`, `supervised` and `complex`. Common functions for computation and extraction of results and plotting are found in `multiblock_results` and `multiblock_plots`, respectively.
 ```1 2 3 4``` ```data(candies) candyList <- lapply(1:nlevels(candies\$candy),function(x)candies\$assessment[candies\$candy==x,]) can.statis <- statis(candyList) plot(scores(can.statis), labels="names") ```