Description Usage Arguments Value Note Author(s) Examples
Each construct and element are vectors in a multidimensional space. When reducing the representation to a lower dimensional space, a loss of information (sumofsquares) will usually occur. The output of the function shows the proportion of sumofsquares (SSQ) explained for the elements (constructs) and the amount explained by each principal component. This allows to assess which elements (construct) are represented how well in the current representation. Also it shows how much of the total variation is explained.
1 2 3 4 5 6 7 8 9 10 11 
x 

along 
Numeric. Table of sumofsquares (SSQ) for 1=constructs,
2=elements (default).
Note that currently these calculations only make sense
for biplot reperesentations with 
center 
Numeric. The type of centering to be performed.
0= no centering, 1= row mean centering (construct),
2= column mean centering (elements), 3= doublecentering (construct and element means),
4= midpoint centering of rows (constructs).
The default is 
normalize 
A numeric value indicating along what direction (rows, columns)
to normalize by standard deviations. 
g 
Power of the singular value matrix assigned to the left singular vectors, i.e. the constructs. 
h 
Power of the singular value matrix assigned to the right singular vectors, i.e. the elements. 
col.active 
Columns (elements) that are no supplementary points, i.e. they are used in the SVD to find principal components. default is to use all elements. 
col.passive 
Columns (elements) that are supplementary points, i.e. they are NOT used
in the SVD but projecte into the component space afterwards. They do not
determine the solution. Default is 
A list containing three wo elements
ssq.table 
dataframe with sumofsquares explained for element/construct by each dimension 
ssq.table.cumsum 
dataframe with cumulated sumofsquares explained for element/construct number of dimensions 
ssq.total 
total sumofsquares after pretransforming grid matrix 
TODO: if g or h is not equal to 1 the SSQ does not measure accuracy of representation as currently the ssq of each point are set in constrast with the pretransformed matrix.
Mark Heckmann
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21  # explained sumofsquares for elements
ssq(bell2010)
# explained sumofsquares for constructs
ssq(bell2010, along=1)
# save results
s < ssq(bell2010)
# printing options
print(s)
print(s, digits=4)
print(s, dim=3)
print(s, cumulated=FALSE)
# access results
names(s)
s$ssq.table
s$ssq.table.cumsum
s$ssq.total

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