print method for causal_order_stability
Source:R/causal_order_stability.r
print.causal_order_stability.Rdprint method for causal_order_stability
Usage
# S3 method for class 'causal_order_stability'
print(x, ...)Examples
dat <- generate_lingam_sample_6()
bs <- lingam_direct_bootstrap(dat$data, n_sampling = 30L, reg_method = "ols", seed = 42)
#> Bootstrap: 30 iterations, method=ols (sequential)
#> iteration 1 / 30
#> iteration 10 / 30
#> iteration 20 / 30
#> iteration 30 / 30
#> Completed in 0.2 seconds.
print(get_causal_order_stability(bs, labels = names(dat$data)))
#> === Causal Order Stability ===
#> Bootstrap samples: 30
#> Overall stability score: 0.680 (0 = random, 1 = fully stable)
#>
#> Rank summary (sorted by mean rank; 1 = most upstream):
#> variable mean_rank sd_rank median_rank mode_rank
#> x3 1.17 0.91 1.0 1
#> x0 2.57 0.57 3.0 3
#> x2 2.93 0.98 2.5 2
#> x5 4.33 1.32 4.0 3
#> x4 4.87 0.86 5.0 5
#> x1 5.13 1.11 5.0 6
#>
#> Precedence probability P[i, j] = P(variable i precedes j):
#> x0 x1 x2 x3 x4 x5
#> x0 0.00 0.97 0.47 0.03 0.97 1.00
#> x1 0.03 0.00 0.03 0.03 0.40 0.37
#> x2 0.53 0.97 0.00 0.03 0.97 0.57
#> x3 0.97 0.97 0.97 0.00 0.97 0.97
#> x4 0.03 0.60 0.03 0.03 0.00 0.43
#> x5 0.00 0.63 0.43 0.03 0.57 0.00