The results of singular value decomposition of a matrix
of text profiles are displayed in two or three
dimensions.

Note that for easier viewing, configurations are rescaled by
their largest absolute coordinate value:

Consider a document vector passing through a configuration of stimulus points with orthogonal lines drawn from the points on to it. It is the values given to the points at which these orthogonal lines meet the vector which are maximally correlated with the data for that document. The document vectors are normalised (for convenience only) to the same length, so that their ends lie at a common distance from the origin of the space, forming a circle, or sphere, according to the number of dimensions plotted.

The measure of goodness-of-fit of the fitted model to the original data (the "first scores") is the product-moment correlation.