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Generate random graph

Source: R/graph_random.R
graph_random.Rd

Generate a random graph, consisting of a vector of hypothesis weights and a transition matrix. The weights and transition matrix are randomly generated respecting any constraints provided, ensuring that the sum of the weights equals 1 and each row of the transition matrix sums to 1.

Usage

graph_random(m = NULL, graph_constraint = NULL, names = "auto")

Arguments

m

An integer representing the number of hypotheses. It defines both the length of the weight vector and the dimensions (m x m) of the transition matrix. Optional when graph_constraint is supplied (inferred from constraint dimensions). If both m and graph_constraint are supplied, they must agree.

graph_constraint

An optional graph constraint object created by graph_constraint(). When supplied, fixed elements are honoured and only free (NA) positions are randomised.

names

An optional character vector containing hypotheses' names. If not provided it defaults to "auto" meaning the hypotheses will be automatically named "H1", "H2", etc.

Value

A list containing:

  • hyp_weight: A numeric vector of length m representing the generated hypothesis weights.

  • trans_matrix: A numeric matrix of dimension m x m representing the generated transition matrix.

Examples

# Generate a random graph for 5 hypotheses
random_graph <- graph_random(5)

# print the weight vector
random_graph$hyp_weight
#>         H1         H2         H3         H4         H5 
#> 0.34995750 0.18347771 0.02713369 0.26768173 0.17174937 

# print the transition matrix
random_graph$trans_matrix
#>            H1        H2         H3        H4        H5
#> H1 0.00000000 0.1970907 0.02826882 0.1035610 0.6710795
#> H2 0.33323627 0.0000000 0.29235191 0.0588705 0.3155413
#> H3 0.09436979 0.2198000 0.00000000 0.2900734 0.3957568
#> H4 0.20755374 0.2837108 0.31231181 0.0000000 0.1964237
#> H5 0.22885255 0.2476563 0.19637350 0.3271177 0.0000000

# Generate a random graph respecting constraints
gc <- graph_constraint(
    hyp_constraint = c(0.5, NA, NA),
    trans_constraint = matrix(c(0, NA, NA, NA, 0, NA, NA, NA, 0), 3, 3)
)

random_graph <- graph_random(graph_constraint = gc)
random_graph
#> $hyp_weight
#>        H1        H2        H3 
#> 0.5000000 0.2642026 0.2357974 
#> 
#> $trans_matrix
#>           H1        H2        H3
#> H1 0.0000000 0.4271691 0.5728309
#> H2 0.3382072 0.0000000 0.6617928
#> H3 0.2538808 0.7461192 0.0000000
#>