Returns the ssdsims_cost_calibration object shipped with the package - the
calibration fitted during development (see
ssd_cost_calibration_default) and used by ssd_estimate_cost() when no
calibration is supplied. Because the coefficients are architecture-specific,
an estimate built on this default is a ballpark sized for the machine in its
provenance; rerun ssd_calibrate_cost() on your own machine for a
trustworthy estimate.
See also
ssd_calibrate_cost() to re-fit on a target machine and
ssd_estimate_cost() to apply a calibration to a scenario.
Examples
ssd_cost_calibration()
#> <ssdsims_cost_calibration>
#> per-ci_method cost model time = (base + slope * max(nboot, n0)) * nrow_factor
#> weighted_samples base 0.58s 5.50 ms/boot n0 0
#> arithmetic_samples base 1.00s 18.01 ms/boot n0 25
#> MACL base 0.92s 18.35 ms/boot n0 25
#> GMACL base 0.91s 18.36 ms/boot n0 25
#> geometric_samples base 0.95s 18.48 ms/boot n0 25
#> multi_free base 0.18s 40.05 ms/boot n0 0
#> multi_fixed base 0.15s 40.68 ms/boot n0 0
#> nrow_factor: 5:0.27 10:1.09 20:1.34 50:0.82
#> fixed_addend: 0.05s (sample + fit per task)
#> provenance:
#> cpu: Intel(R) Xeon(R) Processor @ 2.10GHz
#> R: R version 4.5.3 (2026-03-11)
#> ssdtools: 2.6.0.9002
#> date: 2026-06-07
#> sweep: nboot {20, 50, 100, 200} x nrow {5, 10, 20, 50} x 7 ci_methods
#> Ballpark only: coefficients are architecture-specific - recalibrate with
#> ssd_calibrate_cost() on the target machine for a trustworthy estimate.
#>