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Fit the model over a ladder of K

Source: R/ladder.R
fit_ladder.Rd

Fits fit_bayesian() at each K in the ladder and stores, per rung, the fit together with the adequacy and support evidence that select_k() consumes. Expect roughly one full fit's runtime per rung; a message up front says how many rungs are coming.

Usage

fit_ladder(
  Y,
  K_max = NULL,
  K_min = 2,
  q = 0.05,
  screen_draws = 30,
  screen_mixes = 60,
  quiet = FALSE,
  ...
)

Arguments

Y

As in fit_bayesian().

K_max

Largest K to fit. NULL (default) uses min(6, floor(N / 3)), capped at 3 when N <= 12 — with a dozen sorts or fewer, the data cannot formally discriminate adjacent K.

K_min

Smallest K to fit (default 2).

q

False-discovery level for the support evidence stored on each rung (default 0.05); select_k() can re-select at another q.

screen_draws, screen_mixes

Budget for the per-rung person check (defaults 30 and 60; the cluster signal needs no more).

quiet

Suppress per-rung messages (default FALSE).

...

Passed to fit_bayesian() (iterations, seed, ...).

Value

A bayesqm_ladder: the per-rung fits and evidence.