Normalizes the selected Configuration.
With the default value (0.0) for sumOfSquares, and eachDimensionSeparately chosen, an INDSCAL-like normalization is applied: the sum of squares for each column is scaled to equal 1.0. When eachDimensionSeparately is off, a Kruskal-like normalization is applied: the sum of squares of the whole matrix is scaled equal to numberOfRows.
Before the normalization will be applied, however, we first translate the centre of the configuration to the origin by subtracting the mean for each dimension. The sum of squares than equals variance.
© djmw, April 7, 2004