Select the k first components and their complement as initial cliques

This function aims at efficiently exploring the space of likely cliques when only one missing actor is estimated. It focuses and the first two principal component axes found, and their complements.

complement_spca(M, k)

Arguments

M	Gaussian proxy for the original dataset. Possibly obtained using PLNmodels.
k	Number of principal components of sparse PCA to keep.

Value

A list of 2 x k cliques.

Examples

data=generate_missing_data(n=100,p=10,r=1,type="scale-free", plot=TRUE)
PLNfit=norm_PLN(data$Y)
data$TC
#> [[1]]
#> [1] 1 2 4 8
#> 
complement_spca(PLNfit$MO,k=2)
#> [[1]]
#> [[1]][[1]]
#> [1]  1  7  8 10
#> 
#> 
#> [[2]]
#> [[2]][[1]]
#> [1] 3 5 6 9
#> 
#> 
#> [[3]]
#> [[3]][[1]]
#> [1] 2 3 4 5 6 9
#> 
#> 
#> [[4]]
#> [[4]][[1]]
#> [1]  1  2  4  7  8 10
#> 
#>