htna-named wrapper for Nestimate::net_reprune(). Re-applies the
pruning rule recorded on a network (e.g. after the weights have been
re-estimated), without having to restate the rule.
Arguments
- x
An htna network carrying a prior pruning rule (or other object accepted by
Nestimate::net_reprune()); S3 dispatch onxis preserved.- ...
Additional arguments passed to
Nestimate::net_reprune(). See that function for details.
Value
The re-pruned htna network. See Nestimate::net_reprune().
Details
The actor partition ($node_groups, $actor_levels, htna class)
is preserved, so the re-pruned network stays htna-aware.
Suffixed _htna to avoid clashing with the tna verb reprune() and
to sit alongside the rest of the htna API.
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)
pruned <- prune_htna(net, method = "threshold", threshold = 0.05)
reprune_htna(deprune_htna(pruned))
#> Transition Network (relative probabilities) [directed]
#> Weights: [0.003, 0.611] | mean: 0.146
#>
#> Weight matrix:
#> Ask Check Delegate Execute Frustrate Inquire Plan Refine Repair
#> Ask 0.018 0.063 0 0.000 0.116 0.063 0.409 0.051 0.000
#> Check 0.117 0.050 0 0.411 0.058 0.000 0.000 0.000 0.000
#> Delegate 0.000 0.000 0 0.000 0.110 0.000 0.611 0.000 0.000
#> Execute 0.061 0.087 0 0.074 0.143 0.088 0.107 0.069 0.000
#> Frustrate 0.194 0.104 0 0.119 0.114 0.060 0.000 0.098 0.000
#> Inquire 0.251 0.069 0 0.285 0.000 0.033 0.000 0.000 0.000
#> Plan 0.000 0.146 0 0.000 0.215 0.083 0.003 0.086 0.000
#> Refine 0.143 0.000 0 0.206 0.000 0.000 0.000 0.000 0.000
#> Repair 0.241 0.000 0 0.391 0.000 0.000 0.000 0.000 0.004
#> Report 0.102 0.114 0 0.000 0.124 0.102 0.000 0.058 0.000
#> Request 0.148 0.055 0 0.292 0.000 0.000 0.000 0.000 0.000
#> Specify 0.269 0.000 0 0.273 0.096 0.000 0.000 0.000 0.000
#> Report Request Specify
#> Ask 0.000 0.173 0.052
#> Check 0.055 0.000 0.156
#> Delegate 0.000 0.131 0.000
#> Execute 0.000 0.293 0.065
#> Frustrate 0.000 0.135 0.085
#> Inquire 0.170 0.000 0.000
#> Plan 0.000 0.325 0.095
#> Refine 0.000 0.105 0.413
#> Repair 0.103 0.071 0.000
#> Report 0.077 0.257 0.066
#> Request 0.000 0.067 0.336
#> Specify 0.000 0.126 0.101
#>
#> Initial probabilities:
#> Specify 0.818 ████████████████████████████████████████
#> Request 0.156 ████████
#> Frustrate 0.023 █
#> Refine 0.002
#> Ask 0.000
#> Check 0.000
#> Delegate 0.000
#> Execute 0.000
#> Inquire 0.000
#> Plan 0.000
#> Repair 0.000
#> Report 0.000
# }