Print Reliability Analysis Results

Print Reliability Analysis Results

Usage

# S3 method for class 'tna_reliability'
print(x, summary_metrics, ...)

Arguments

x

A tna_reliability object.

summary_metrics

A character vector of metrics to display.

...

Arguments passed to the generic print method.

Value

x (invisibly).

See also

Validation functions bootstrap(), deprune(), estimate_cs(), permutation_test(), permutation_test.group_tna(), plot.group_tna_bootstrap(), plot.group_tna_permutation(), plot.group_tna_stability(), plot.tna_bootstrap(), plot.tna_permutation(), plot.tna_reliability(), plot.tna_stability(), print.group_tna_bootstrap(), print.group_tna_permutation(), print.group_tna_stability(), print.summary.group_tna_bootstrap(), print.summary.tna_bootstrap(), print.tna_bootstrap(), print.tna_clustering(), print.tna_permutation(), print.tna_stability(), prune(), pruning_details(), reliability(), reprune(), summary.group_tna_bootstrap(), summary.tna_bootstrap()

Examples

# Small number of iterations for CRAN
model <- tna(engagement)
rel <- reliability(model, iter = 20)
print(rel)
#> Reliability summary
#> # A tibble: 4 × 8
#>   metric               mean       sd  median     min    max     q25     q75
#>   <chr>               <dbl>    <dbl>   <dbl>   <dbl>  <dbl>   <dbl>   <dbl>
#> 1 Mean Abs. Diff.   0.00731 0.00262  0.00656 0.00374 0.0127 0.00518 0.00911
#> 2 Median Abs. Diff. 0.00603 0.00248  0.00498 0.00314 0.0104 0.00423 0.00732
#> 3 Pearson           1.000   0.000316 1.000   0.999   1.000  0.999   1.000  
#> 4 Bray-Curtis       0.0110  0.00393  0.00984 0.00561 0.0190 0.00777 0.0137