A grid of simulation scenarios

Builds the scenario grid a simulation study varies over, as data rather than as nested loops, so it can be inspected, filtered, subsetted and passed straight to cpt_benchmark().

Usage

cpt_scenarios(
  n = 500,
  jump = c(0.5, 1, 2),
  location = 0.5,
  noise = "gauss",
  rho = 0.5,
  change_in = "mean",
  n_rep = 1,
  seed = 1,
  as_datasets = TRUE
)

Arguments

n

Series lengths.

jump

Change sizes, in standard deviations.

location

Change positions, as fractions of n.

noise

Noise models; any value cpt_simulate() accepts.

rho

AR(1) parameters (used by noise = "ar1").

change_in

Change types.

n_rep

Replicates per scenario. Defaults to 1.

seed

Base seed; replicate r of scenario i uses seed + (i - 1) * n_rep + r, so the whole grid is reproducible and every cell is independent.

as_datasets

Return simulated datasets in cpt_benchmark()'s shape (the default), or just the scenario table?

Value

A named list of datasets, or a tibble of scenarios when as_datasets = FALSE.

See also

cpt_power(), cpt_benchmark().

Examples

scen <- cpt_scenarios(n = 200, jump = c(1, 3), as_datasets = FALSE)
scen
#> # A tibble: 2 × 7
#>       n  jump location noise change_in   rho scenario          
#>   <int> <dbl>    <dbl> <chr> <chr>     <dbl> <chr>             
#> 1   200     1      0.5 gauss mean          0 mean_n200_j1_gauss
#> 2   200     3      0.5 gauss mean          0 mean_n200_j3_gauss