Simulate sequences from a mixture of transition systems

Usage

simulate_sequence_clusters(
  n,
  transitions,
  chain_length,
  proportions = NULL,
  initial = NULL,
  labels = NULL,
  states = NULL,
  seed = NULL,
  batch = NULL
)

Arguments

n: Number of sequences.
transitions: List of transition matrices, or a tidy data frame with columns cluster, from, to and probability.
chain_length: Sequence length.
proportions: Cluster proportions. When NULL, clusters are equally likely.
initial: Optional common initial probabilities, shared by every cluster. When NULL, every sequence starts in the first state.
labels: Optional sequence-cluster labels.
states: Optional state labels. When the matrices carry no dimnames and states is NULL, states are labeled by their row index.
seed: Optional random seed.
batch: Optional single positive whole number. When given, the simulator runs batch times and returns a plain list of batch results, each exactly what the same call without batch returns. With a seed, every dataset gets its own seed drawn from seed, so the whole batch is reproducible; without one the datasets are consecutive draws from the session's random-number stream. The default NULL returns a single result.

Value

A long-form simulab_sim base data.frame with columns id, period, state, and the true sequence_cluster, one row per sequence position. A transitions table (sequence_cluster, from, to, probability) is available through as.data.frame().

Examples

# One transition matrix per latent cluster.
result <- simulate_sequence_clusters(
  n = 60,
  transitions = list(
    matrix(c(0.8, 0.2, 0.3, 0.7), nrow = 2, byrow = TRUE),
    matrix(c(0.3, 0.7, 0.6, 0.4), nrow = 2, byrow = TRUE)
  ),
  chain_length = 12,
  seed = 1
)
head(result)
#> <simulab_sim:sequence_clusters> 6 rows x 4 columns
#>   id period state   sequence_cluster
#> 1  1      1     1 Sequence cluster 2
#> 2  1      2     2 Sequence cluster 2
#> 3  1      3     1 Sequence cluster 2
#> 4  1      4     2 Sequence cluster 2
#> 5  1      5     2 Sequence cluster 2
#> 6  1      6     1 Sequence cluster 2
#> 
#> Truth (transitions):
#>     sequence_cluster from to probability
#> 1 Sequence cluster 1    1  1         0.8
#> 2 Sequence cluster 1    2  1         0.3
#> 3 Sequence cluster 1    1  2         0.2
#> 4 Sequence cluster 1    2  2         0.7
#> 5 Sequence cluster 2    1  1         0.3
#> 6 Sequence cluster 2    2  1         0.6
#> 7 Sequence cluster 2    1  2         0.7
#> 8 Sequence cluster 2    2  2         0.4
components(result)
#>         table rows columns
#> 1        data  720       4
#> 2 transitions    8       4