Fit TNA models to multiple datasets

Usage

fit_tna_batch(inputs, ...)

Arguments

inputs: List of sequence data frames, with at least one element. Element names label the datasets; when inputs is unnamed the labels "Dataset 1", "Dataset 2", ... are used instead.
...: Arguments passed to fit_tna().

Value

A simulab_sim edge list with one row per dataset and transition: a leading dataset column followed by the columns fit_tna() returns (from, to, weight, and group when a grouped fit is requested). The model_info component holds one row per dataset describing the fitted model.

Examples

inputs <- list(
  first = simulate_sequences(n = 30, n_states = 3, chain_length = 10, seed = 1),
  second = simulate_sequences(n = 30, n_states = 3, chain_length = 10, seed = 2)
)
if (requireNamespace("tna", quietly = TRUE)) {
  head(fit_tna_batch(inputs, model = "tna"))
}
#> <simulab_sim:tna_batch> 6 rows x 4 columns
#>         dataset    from    to     weight
#> first.1   first   Learn Learn 0.56849315
#> first.2   first    Plan Learn 0.23809524
#> first.3   first Reflect Learn 0.86585366
#> first.4   first   Learn  Plan 0.04794521
#> first.5   first    Plan  Plan 0.21428571
#> first.6   first Reflect  Plan 0.08536585
#> 
#> Other tables: model_info. Read one with as.data.frame(x, what = "model_info").