Returns the top n pathways by Kullback-Leibler divergence
from their (k-1)-suffix. These are the pathways whose extended
history adds the most predictive information over the shorter one.
Pathways whose most likely next state actually flips between orders
are marked in the changes_prediction column.
Value
A data.frame, same columns as tree_pathways,
sorted by divergence descending.
Examples
# \donttest{
seqs <- replicate(50, sample(c("A","B","C"), 12, replace = TRUE),
simplify = FALSE)
tree <- context_tree(seqs, max_depth = 3)
divergent_pathways(tree, top = 6)
#> pathway depth count likely_next next_probability divergence
#> 1 A -> A -> B 3 12 A 0.5825833 0.5737596
#> 2 C -> A -> B 3 19 C 0.5263158 0.2240645
#> 3 A -> B -> A 3 14 B 0.5714286 0.2173227
#> 4 B -> C -> A 3 17 A 0.5882353 0.1732741
#> 5 B -> B -> A 3 17 A 0.4705882 0.1606417
#> 6 C -> C -> B 3 12 B 0.5000000 0.1107270
#> changes_prediction
#> 1 TRUE
#> 2 TRUE
#> 3 TRUE
#> 4 FALSE
#> 5 FALSE
#> 6 FALSE
divergent_pathways(tree, flips_only = TRUE)
#> pathway depth count likely_next next_probability divergence
#> 1 A -> A -> B 3 12 A 0.5825833 0.57375959
#> 2 C -> A -> B 3 19 C 0.5263158 0.22406455
#> 3 A -> B -> A 3 14 B 0.5714286 0.21732269
#> 7 C -> A -> A 3 21 A 0.4761905 0.10217770
#> 8 A -> C -> A 3 21 B 0.4285714 0.09413230
#> 11 B -> A -> C 3 13 B 0.5384615 0.06615899
#> 12 C -> B -> A 3 13 C 0.4615385 0.06590266
#> 15 C -> B -> C 3 18 A 0.4444444 0.05257821
#> 17 A -> A -> A 3 20 B 0.4000000 0.04762184
#> 18 B -> C -> B 3 23 C 0.4347826 0.04672169
#> changes_prediction
#> 1 TRUE
#> 2 TRUE
#> 3 TRUE
#> 7 TRUE
#> 8 TRUE
#> 11 TRUE
#> 12 TRUE
#> 15 TRUE
#> 17 TRUE
#> 18 TRUE
# }