Simulate a binary error stream with a known drift point

Generates a stream of 0/1 classifier errors whose error rate jumps from p_pre to p_post after n_pre observations. Useful for testing and validating drift detectors against a known ground truth.

Usage

sim_drift_stream(
  n_pre = 500,
  n_post = 500,
  p_pre = 0.05,
  p_post = 0.3,
  seed = NULL
)

Arguments

n_pre, n_post

Number of observations before / after the drift point.

p_pre, p_post

Error probability before / after the drift point.

seed

Optional integer; if supplied, set.seed() is called for reproducibility.

Value

A tibble with columns t (index), error (0/1) and drift_true (logical ground truth: TRUE after the drift point).

Examples

sim_drift_stream(n_pre = 100, n_post = 100, seed = 42)
#> # A tibble: 200 × 3
#>        t error drift_true
#>    <int> <int> <lgl>     
#>  1     1     0 FALSE     
#>  2     2     0 FALSE     
#>  3     3     0 FALSE     
#>  4     4     0 FALSE     
#>  5     5     0 FALSE     
#>  6     6     0 FALSE     
#>  7     7     0 FALSE     
#>  8     8     0 FALSE     
#>  9     9     0 FALSE     
#> 10    10     0 FALSE     
#> # ℹ 190 more rows