Generate simulation parameters from a graph adjacency matrix

Generate simulation parameters from a graph adjacency matrix

generator_param(G, signed = FALSE, v = 0.01)

Arguments

G	adjacency matrix
signed	boolean: should the graph be composed of positive and negative partial correlations ?
v	parameter controlling the noise on the precision matrix

Value

a list containing

• sigma: the covariance matrix

• omega: the precision matrix

• lambda: the constant that was needed to load the diagonal of omega and ensure its positive definiteness

Examples

G<-generator_graph(p=10,graph="tree")
generator_param(G=G)
#> $sigma
#>             [,1]       [,2]       [,3]       [,4]       [,5]       [,6]
#>  [1,]  10.611521  10.108061  10.019818  -9.638101 -10.209141   9.829909
#>  [2,]  10.108061  11.561710   9.544431  -9.180825 -10.677327   9.363532
#>  [3,]  10.019818   9.544431  11.386098  -9.999951  -9.639875  10.198960
#>  [4,]  -9.638101  -9.180825  -9.999951  11.533275   9.272633 -10.762799
#>  [5,] -10.209141 -10.677327  -9.639875   9.272633  10.784100  -9.457167
#>  [6,]   9.829909   9.363532  10.198960 -10.762799  -9.457167  10.976989
#>  [7,]  -9.910825 -10.365331  -9.358193   9.001682  10.468984  -9.180825
#>  [8,]  10.009934  10.468984   9.451775  -9.091699 -10.573674   9.272633
#>  [9,] -10.120016  -9.639875 -10.499958  10.099951   9.736274 -10.300950
#> [10,]   9.542674   9.089925   9.900942 -11.419085  -9.180825  10.656237
#>             [,7]       [,8]       [,9]      [,10]
#>  [1,]  -9.910825  10.009934 -10.120016   9.542674
#>  [2,] -10.365331  10.468984  -9.639875   9.089925
#>  [3,]  -9.358193   9.451775 -10.499958   9.900942
#>  [4,]   9.001682  -9.091699  10.099951 -11.419085
#>  [5,]  10.468984 -10.573674   9.736274  -9.180825
#>  [6,]  -9.180825   9.272633 -10.300950  10.656237
#>  [7,]  12.114342 -11.235486   9.451775  -8.912557
#>  [8,] -11.235486  11.347841  -9.546293   9.001682
#>  [9,]   9.451775  -9.546293  10.604958  -9.999951
#> [10,]  -8.912557   9.001682  -9.999951  12.296123
#> 
#> $omega
#> 10 x 10 sparse Matrix of class "dsCMatrix"
#>                                                        
#>  [1,] 2.01 .    .    .    1.00 .    .    .    1.00 .   
#>  [2,] .    1.01 .    .    1.00 .    .    .    .    .   
#>  [3,] .    .    1.01 .    .    .    .    .    1.00 .   
#>  [4,] .    .    .    2.01 .    1.00 .    .    .    1.00
#>  [5,] 1.00 1.00 .    .    3.01 .    .    1.00 .    .   
#>  [6,] .    .    .    1.00 .    2.01 .    .    1.00 .   
#>  [7,] .    .    .    .    .    .    1.01 1.00 .    .   
#>  [8,] .    .    .    .    1.00 .    1.00 2.01 .    .   
#>  [9,] 1.00 .    1.00 .    .    1.00 .    .    3.01 .   
#> [10,] .    .    .    1.00 .    .    .    .    .    1.01
#> 
#> $lambda
#> [1] 1
#>