Simulates a graph

This is an internal simulation function. It creates a graph with regression coefficients.

sim_B(p, graph_setting, l, u, unique_ordering = TRUE)

Arguments

p	number of variables to simulate
graph_setting	either "dense", "sparse", "A", or "B". These settings correspons to the settings described in the article.
l	lower bound for direct abolute causal effect
u	upper bound for direct absolute causal effect
unique_ordering	if TRUE the simulated graph will have a unique topological ordering

Value

Returns a matrix of size p times p encoding a graph with regression coefficients.

Details

The sim_B function simulates a causal graph with regression coefficients. The graph is stored as matrix, where the (i,j)th entry in the matrix is non zero only if there is an arrow from j to i in the graph. The value in the (i,j)th entry corresponds to the direct causal effect from j to i.

Examples

sim_B(5, "dense", 0.3, 1)
#>      [,1]       [,2]      [,3]       [,4]       [,5]
#> [1,]    0 -0.7110621 0.0000000  0.0000000  0.8558501
#> [2,]    0  0.0000000 0.6923577  0.0000000  0.4479231
#> [3,]    0  0.0000000 0.0000000 -0.3032418  0.0000000
#> [4,]    0  0.0000000 0.0000000  0.0000000 -0.9181873
#> [5,]    0  0.0000000 0.0000000  0.0000000  0.0000000

sim_B(5, "sparse", 0.7, 1, uniqe_ordering = FALSE)
#> Error in sim_B(5, "sparse", 0.7, 1, uniqe_ordering = FALSE): ubrugt argument (uniqe_ordering = FALSE)