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Test the Markov order of sequences

Source: R/memory_wrappers.R
markov_order.Rd

At each order k the likelihood-ratio statistic G2 tests whether the k-th state back adds information about the next state given the k - 1 most recent ones; its null distribution comes from an exact within-context permutation. The order is raised while the test rejects.

Usage

markov_order(
  data,
  max_order = 3L,
  n_perm = 500L,
  alpha = 0.05,
  parallel = FALSE,
  n_cores = 2L,
  seed = NULL,
  action = NULL,
  actor = NULL,
  time = NULL,
  session = NULL,
  time_threshold = 900,
  timezone = "UTC"
)

Arguments

data

Sequences in any form described in sequence-input; a netobject_group gives one test per group.

max_order

Integer. Highest order tested. Default 3.

n_perm

Integer. Permutations per order. Default 500.

alpha

Significance level of the sequential selection. Default 0.05.

parallel

Logical. Run the permutations with parallel::mclapply() (not on Windows). Default FALSE.

n_cores

Integer. Cores when parallel = TRUE. Default 2.

seed

Integer or NULL. Seed for the permutations.

action, actor, time, session, time_threshold, timezone

Long-format arguments (see sequence-input); leave the column names NULL for wide, list or model input.

Value

A net_markov_order object (a net_markov_order_group for a netobject_group). Read it with hg_get(): the per-order test table (what = "orders", the default) or the permutation null draws ("null").

References

Anderson, T. W., & Goodman, L. A. (1957). Statistical inference about Markov chains. The Annals of Mathematical Statistics, 28(1), 89–110. doi:10.1214/aoms/1177707039

Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer.

See also

mogen(), memory()

Examples

seqs <- list(c("a", "b", "a", "c", "a", "b"), c("b", "a", "c", "a", "b", "a"))
fit <- markov_order(seqs, max_order = 2L, n_perm = 20L, seed = 1L)
hg_get(fit)
#>   order log_likelihood      aic      bic df        g2    p_value p_asymptotic
#> 1     0     -12.136851 28.27370 29.24352 NA        NA         NA           NA
#> 2     1      -5.156818 16.31364 17.76836  4 13.862944 0.04761905  0.007745578
#> 3     2      -2.302585 10.60517 12.05989  1  5.545177 0.52380952  0.018531678
#>   significant
#> 1          NA
#> 2        TRUE
#> 3       FALSE