statis {ClustBlock} R Documentation

## Performs the STATIS method on different blocks of quantitative variables

### Description

STATIS method on quantitative blocks. SUpplementary outputs are also computed

### Usage

```statis(Data,Blocks,NameBlocks=NULL,Graph_obj=TRUE, Graph_weights=TRUE, scale=FALSE)
```

### Arguments

 `Data` data frame or matrix. Correspond to all the blocks of variables merged horizontally `Blocks` numerical vector. The number of variables of each block. The sum must be equal to the number of columns of Data `NameBlocks` string vector. Name of each block. Length must be equal to the length of Blocks vector. If NULL, the names are B1,...Bm. Default: NULL `Graph_obj` logical. Show the graphical representation od the objects? Default: TRUE `Graph_weights` logical. Should the barplot of the weights be plotted? Default: TRUE `scale` logical. Should the data variables be scaled? Default: FALSE

### Value

a list with:

• RV: the RV matrix: a matrix with the RV coefficient between blocks of variables

• compromise: a matrix which is the compromise of the blocks (akin to a weighted average)

• weights: the weights associated with the blocks to build the compromise

• lambda: the first eigenvalue of the RV matrix

• overall error : the error for the STATIS criterion

• error_by_conf: the error by configuration (STATIS criterion)

• rv_with_compromise: the RV coefficient of each block with the compromise

• homogeneity: homogeneity of the blocks (in percentage)

• coord: the coordinates of each object

• eigenvalues: the eigenvalues of the svd decomposition

• inertia: the percentage of total variance explained by each axis

• error_by_obj: the error by object (STATIS criterion)

• scalefactors: the scaling factors of each block

• proj_config: the projection of each object of each configuration on the axes: presentation by configuration

• proj_objects: the projection of each object of each configuration on the axes: presentation by object

### References

• Lavit, C., Escoufier, Y., Sabatier, R., Traissac, P. (1994). The act (statis method). Computational 462 Statistics & Data Analysis, 18 (1), 97-119.\

• Llobell, F., Cariou, V., Vigneau, E., Labenne, A., & Qannari, E. M. (2018). Analysis and clustering of multiblock datasets by means of the STATIS and CLUSTATIS methods.Application to sensometrics. Food Quality and Preference, in Press.

`plot.statis`, `clustatis`

### Examples

```
data(smoo)
NameBlocks=paste0("S",1:24)
st=statis(Data=smoo, Blocks=rep(2,24),NameBlocks = NameBlocks)
summary(st)
#with variables scaling
st2=statis(Data=smoo, Blocks=rep(2,24),NameBlocks = NameBlocks, Graph_weights=FALSE, scale=TRUE)

```

[Package ClustBlock version 2.4.0 Index]