Return a data frame summarising all registered network estimators.
Examples
list_estimators()
#> name description
#> 1 attention Decay-weighted attention transitions
#> 2 co_occurrence Co-occurrence within sequences
#> 3 cor Pairwise correlation network
#> 4 frequency Raw transition frequency counts
#> 5 gap Gap-allowed transitions weighted by 1/distance
#> 6 glasso EBICglasso regularized partial correlations
#> 7 ising Ising model (L1-penalized logistic regression)
#> 8 mgm Mixed Graphical Model (nodewise lasso, EBIC, LW threshold)
#> 9 ngram n-gram transitions (adjacent pairs per n-gram window)
#> 10 pcor Unregularized partial correlations
#> 11 relative Row-normalized transition probabilities
#> 12 reverse Reverse (reply) transitions: transpose of frequency
#> 13 wtna Window-based TNA transitions (one-hot)
#> 14 wtna_cooccurrence Window-based TNA co-occurrence (one-hot)
#> directed
#> 1 TRUE
#> 2 FALSE
#> 3 FALSE
#> 4 TRUE
#> 5 TRUE
#> 6 FALSE
#> 7 FALSE
#> 8 FALSE
#> 9 TRUE
#> 10 FALSE
#> 11 TRUE
#> 12 TRUE
#> 13 TRUE
#> 14 FALSE