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Table 4 For each method, the first two columns show the number of nonzero elements in the first two estimated coefficient loadings of three datasets, the Affymetrix, the Agilent, and the protein dataset respectively. Next four columns contain pseudo-eigenvalues calculated using the estimated coefficient loadings from the training dataset. Last four columns include proportions of pseudo-eigenvalues to the sum of total eigenvalues for each dataset

From: Sparse multiple co-Inertia analysis with application to integrative analysis of multi -Omics data

 # of nonzerosPseudo Eigenvalues% of variability explained
   test datasetwhole datasettest datasetwhole dataset
 1st2nd1st1st + 2nd1st1st + 2nd1st1st + 2nd1st1st + 2nd
mCIA(491,488,94)(491,488,94)36065.9233447.03282991.70218372.500.0880.1690.1290.229
smCIA(250,30,20)(100,80,15)31161.8921283.77208966.30157045.800.0760.1270.0950.167
ssmCIA(300,80,15)(400,15,30)34611.1136793.08239050.80239050.800.0840.1730.1090.218