estimation_iteration_report: Build an estimation-iteration report (preferred alias)

In mfrmr: Estimation and Diagnostics for Many-Facet Measurement Models

Build an estimation-iteration report (preferred alias)

Description

Build an estimation-iteration report (preferred alias)

Usage

estimation_iteration_report(
  fit,
  max_iter = 20,
  reltol = NULL,
  include_prox = TRUE,
  include_fixed = FALSE
)

Arguments

fit	Output from fit_mfrm().
max_iter	Maximum replay iterations (excluding optional initial row).
reltol	Stopping tolerance for replayed max-logit change.
include_prox	If TRUE, include an initial pseudo-row labeled PROX.
include_fixed	If TRUE, include a legacy-compatible fixed-width text block.

Details

summary(out) is supported through summary(). plot(out) is dispatched through plot() for class mfrm_iteration_report (type = "residual", "logit_change", "objective").

Value

A named list with iteration-report components. Class: mfrm_iteration_report.

Interpreting output

• iterations: trajectory of convergence indicators by iteration.

• summary: final status and stopping diagnostics.

• optional PROX row: pseudo-initial reference point when enabled.

Typical workflow

1. Run estimation_iteration_report(fit).

2. Inspect plateau/stability patterns in summary/plot.

3. Adjust optimization settings if convergence looks weak.

See Also

fit_mfrm(), specifications_report(), data_quality_report(), mfrmr_reports_and_tables, mfrmr_compatibility_layer

Examples

toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 25)
out <- estimation_iteration_report(fit, max_iter = 5)
summary(out)
p_iter <- plot(out, draw = FALSE)
class(p_iter)

mfrmr documentation built on March 31, 2026, 1:06 a.m.