Benchmark exact-GP scaling — benchmark_exact_gp

Measures exact GP fit time and retained model size over increasing training sizes using seeded RBF simulations. This function is intended for local empirical scaling studies rather than CI performance gating.

Usage

benchmark_exact_gp_scaling(
  sizes = c(50L, 100L, 200L, 400L),
  repeats = 3L,
  seed = 1729L
)

Arguments

sizes: Positive integer vector of training sizes.
repeats: Number of timing repetitions per size.
seed: Base non-negative integer seed.

Value

A data frame with one row per requested size.

Stability

Experimental: this interface may change in a minor release, and every change is listed in NEWS. See gaussianprocesses-package for the policy.

Examples

# A deliberately small run; larger sizes show the cubic cost.
benchmark_exact_gp_scaling(sizes = c(20, 40), repeats = 1)
#>    n median_fit_elapsed_seconds retained_model_bytes numerical_jitter
#> 1 20                      0.003                10680                0
#> 2 40                      0.001                21400                0
#>   reciprocal_condition_number
#> 1                 0.003950969
#> 2                 0.001568076