Summary Statistics for Spectral Map Analysis
Summary method for object of class mpm
.
1 2 
object 
an object of class 
maxdim 
maximum number of principal factors to be reported. Defaults
to 
... 
further arguments; currently none are used 
The function summary.mpm
computes and returns a list of summary
statistics of the spectral map analysis given in x
.
An object of class summary.mpm
with the following components:
call 
the call to 
Vxy 
sum of eigenvalues 
VPF 
a matrix with on the first line the eigenvalues and on the
second line the cumulative eigenvalues of each of the principal factors
( 
Rows 
a data frame with summary statistics for the rowitems, as described below. 
Columns 
a data frame with with summary statistics for the
columnitems, as described below. 
Posit 
binary
indication of whether the row or column was positioned ( 
Weight 
weight applied to the row or column in the
function 
PRF1PRFmaxdim 
factor scores or loadings for
the first 
Resid 
residual score or loading not accounted for by the first

Norm 
length of the vector representing the row or column in factor space. 
Contrib 
contribution of row or column to the sum of eigenvalues. 
Accuracy 
accuracy of the
representation of the row or column by means of the first 
Luc Wouters
Wouters, L., Goehlmann, H., Bijnens, L., Kass, S.U., Molenberghs, G., Lewi, P.J. (2003). Graphical exploration of gene expression data: a comparative study of three multivariate methods. Biometrics 59, 11311140.
1 2 3 4 5 6 7 8 9 10  # Example 1 weighted spectral map analysis Golub data
data(Golub)
r.sma < mpm(Golub[,1:39], row.weight = "mean", col.weight = "mean")
# summary report
summary(r.sma)
# Example 2 using print function
data(Famin81A)
r.fam < mpm(Famin81A, row.weight = "mean", col.weight = "mean")
r.sum < summary(r.fam)
print(r.sum, what = "all")

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