Fuller display of a cpm_fit() object: adds the correlation-function weights,
the full set of fit indices, a residual summary (the largest absolute
residual and the pair it belongs to), and all boundary/identification
diagnostics and the lower-discrepancy note in plain language. When the confidence intervals are analytic,
prints a coverage caution calibrated by simulation: unconditionally when the
sample size is modest (N < 2000, where Wald intervals mis-covered for every
configuration studied), and from N = 2000 up to but not including N = 50000
when the fitted solution shows a
boundary or weak-identification marker (Heywood communality, boundary
harmonic removed, small correlation-function weight, ill-conditioned
Hessian, or competing near-tied optima), the regime where they mis-covered even at large N (see
cpm_fit()). The vignette section When a fit sits at a boundary
(vignette("cpm-boundary-fits")) glosses each marker and
gives the interpretation and next steps when one fires. When the
confidence intervals are bootstrap, any fired markers are instead listed
in a descriptive note at every sample size; the note also states that
what has been measured about the markers covers analytic intervals only
(and not every marker was measured), so they are not validated as
predictors of the bootstrap intervals.
Usage
# S3 method for class 'circumplex_cpm'
summary(object, digits = 3, ...)