Tables of a Markov order test

Usage

# S3 method for class 'net_markov_order'
hg_get(x, what = c("orders", "null"), ..., top = NULL)

Arguments

x: A net_markov_order object from markov_order().
what: "orders" (default) for the per-order test table, or "null" for the permutation null distribution behind it.
...: Additional arguments (ignored).
top: Integer or NULL. Return only the first top rows, applied after any filter and after sort_by, so sort_by and top compose. Default NULL returns every row.

Value

A data.frame. For what = "orders", one row per candidate order: order, log_likelihood, aic, bic, df, g2 (the likelihood-ratio statistic against the order below), p_value (its permutation p-value), p_asymptotic (its chi-squared p-value) and significant. For what = "null", one row per permutation replicate: order, replicate, g2 (the replicate's likelihood-ratio statistic under the null).

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
hg_get(fit, what = "null", top = 5)
#>   order replicate       g2
#> 1     1         1 3.452185
#> 2     1         2 1.726092
#> 3     1         3 3.452185
#> 4     1         4 7.271270
#> 5     1         5 4.498681