A single discoverable entry point over every explicit-parameter
simulator in the package. You pass the simulation type plus the
named arguments that simulator expects, and simulate() forwards them
straight through, returning that simulator's saqr_sim object
unchanged. Use list_simulators to see the available types.
For random, seed-driven generation (where the seed picks both the data and
the structural parameters) and a bare data.frame return, use the
separate simulate_data entry point instead.
Arguments
- type
Character scalar. The simulation type. One of the values in the
typecolumn oflist_simulators:"ttest","anova","correlation","clusters","prediction","regression","lpa","lca","fa","seq_clusters","longitudinal","mlm","growth","irt","survival","hmm".- ...
Named arguments passed straight through to the matching simulator. See the help page of the underlying simulator (e.g.
simulate_ttest) for the arguments it accepts.- seed
Integer or NULL. Random seed, forwarded to the target simulator.
Value
The saqr_sim object returned by the dispatched
simulator (with $data, $params, $type, $seed).
See also
list_simulators for the catalogue of types,
simulate_data for random seed-driven generation.
Examples
simulate("ttest", n_a = 50, n_b = 50, mean_a = 0, mean_b = 0.5, seed = 1)
#> saqr_sim [ttest] 100 x 2 (seed=1)
#> params: mean_a, mean_b, sd_a, sd_b, n_a, n_b, cohens_d
#> cols: group, score
simulate("anova", n = 30, means = c(10, 12, 15), seed = 1)
#> saqr_sim [anova] 90 x 2 (seed=1)
#> params: means, sds, n, labels, eta_squared
#> cols: group, score