htna-named alias of Nestimate::state_distribution(). Returns the
per-timestep distribution of states across sequences, suitable for
driving stacked-area or bar plots.
Value
A data frame with one row per (timestep, state). See
Nestimate::state_distribution() for full details.
Details
Designed with htna in mind: Nestimate ships an explicit
state_distribution.htna S3 method that uses the actor partition
carried by build_htna() networks.
Suffixed _htna to avoid clashing with
Nestimate::state_distribution() when both packages are loaded.
See also
state_frequencies_htna() for the within-network summary.
Examples
# \donttest{
data(human_ai)
net <- build_htna(human_ai, actor_type = "actor_type")
#> Warning: A network with one long sequence is not recommended and can't be validated using bootstrap and other confirmatory testings.
#> Metadata aggregated per session: ties resolved by first occurrence in 'session_date' (1 sessions), 'cluster' (42 sessions), 'actor_type' (24 sessions)
state_distribution_htna(net)
#> group state count proportion
#> 1 AI Execute 3258 0.38100807
#> 2 Human Request 3104 0.28751389
#> 3 Human Specify 2920 0.27047054
#> 4 AI Ask 2416 0.28254005
#> 5 Human Frustrate 1829 0.16941460
#> 6 AI Plan 1620 0.18945153
#> 7 Human Check 1298 0.12022971
#> 8 Human Inquire 853 0.07901074
#> 9 Human Refine 792 0.07336050
#> 10 AI Report 705 0.08244650
#> 11 AI Delegate 295 0.03449889
#> 12 AI Repair 257 0.03005496
# }