Print a simulated transition network — print.simulab

Prints the fitted network with the native tna print method, then the transition matrix and initial probabilities that generated the sequences, in the same format, then the names of the other stored tables.

Usage

# S3 method for class 'simulab_tna'
print(x, digits = 3L, ...)

Arguments

x: A simulab_tna result of simulate_tna().
digits: Digits for the generating probabilities, default 3.
...: Passed to the tna print method.

Value

x, invisibly.

Examples

if (requireNamespace("tna", quietly = TRUE)) {
  print(simulate_tna(n = 30, n_states = 3, seed = 1))
}
#> State Labels : 
#> 
#>    Learn, Plan, Reflect 
#> 
#> Transition Probability Matrix :
#> 
#>             Learn       Plan    Reflect
#> Learn   0.5440252 0.11635220 0.33962264
#> Plan    0.1566265 0.19277108 0.65060241
#> Reflect 0.8934911 0.06508876 0.04142012
#> 
#> Initial Probabilities : 
#> 
#>      Learn       Plan    Reflect 
#> 0.06666667 0.66666667 0.26666667 
#> 
#> Generating Transition Probability Matrix (truth) :
#> 
#>         Learn  Plan Reflect
#> Learn   0.499 0.079   0.422
#> Plan    0.167 0.169   0.664
#> Reflect 0.867 0.071   0.063
#> 
#> Generating Initial Probabilities (truth) :
#> 
#>   Learn    Plan Reflect 
#>   0.038   0.699   0.262 
#> 
#> Other tables: edges, sequences, wide, model_info. Read one with as.data.frame(x, what = "edges").