pcaFS performs Principal Component Analysis (PCA) on raw data.

The main differences with respect to MATLAB function pca are:

1) accepts an input X also as table;

2) produces in table format the percentage of the variance explained single and cumulative of the various components and the associated scree plot in order to decide about the number of components to retain.

3) returns the loadings in table format and shows them graphically.

4) provides guidelines about the automatic choice of the number of components;

5) returns the communalities for each variable with respect to the first k principal components in table format 5) calls app biplotFS which enables to obtain an interactive biplot in which points, rowslabels or arrows can be shown or hidden. This app also gives the possibility of controlling the length of the arrows and the position of the row points through two interactive slier bars.

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use of pcaFS on the ingredients dataset.`out`

=pcaFS(`Y`

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`Name, Value`

)