dot-consensus_target_procrustes_single: Internal single-start GPA-consensus engine
In EFAtools: Fast and Flexible Implementations of Exploratory Factor Analysis Tools

.consensus_target_procrustes_single

R Documentation

Internal single-start GPA-consensus engine

Description

Performs a single GPA-consensus run from one starting target. The multi-start wrapper .gpa_consensus_target() dispatches here.

Usage

.consensus_target_procrustes_single(
  unrotated_list,
  init_targets = NULL,
  rotation = c("orthogonal", "oblique"),
  start = 1,
  tol = 0.001,
  loss_tol = 1e-06,
  loss_patience = 5,
  convergence = c("either", "target", "loss", "both"),
  min_iter = 2,
  max_iter = 200,
  alpha = 1,
  match_target = TRUE,
  hyper_cutoff = 0.15,
  verbose = FALSE
)

Arguments

`unrotated_list`	List of unrotated loading matrices to be aligned. All matrices must be numeric, finite, and have identical dimensions.
`init_targets`	Optional list of starting target matrices. These are typically rotated loading matrices from the corresponding analyses. If `NULL`, `unrotated_list` is used.
`rotation`	Character string, either `"orthogonal"` or `"oblique"`.
`start`	Either a single integer selecting an element of `init_targets`, or an explicit target matrix. Used when `multi_start = FALSE`.
`tol`	Positive relative Frobenius-norm convergence tolerance for the outer target update.
`loss_tol`	Positive tolerance for the relative change in the outer consensus loss. If `NULL`, loss-based convergence is disabled. It cannot be `NULL` when `convergence` is `"loss"` or `"both"`.
`loss_patience`	Positive integer. Number of consecutive iterations with relative loss change below `loss_tol` required for loss-based convergence.
`convergence`	Character string controlling the stopping rule. `"either"` stops when either target or loss convergence is satisfied; `"target"` uses only target change; `"loss"` uses only loss change; `"both"` requires both.
`min_iter`	Non-negative integer. Minimum number of outer iterations before convergence can be declared.
`max_iter`	Positive integer. Maximum number of outer consensus iterations.
`alpha`	Damping factor for the target update. `alpha = 1` uses the full centroid update. Smaller values, such as `0.5`, can reduce oscillation.
`match_target`	Logical. If `TRUE`, the updated centroid is signed and column-matched to the previous target before convergence is evaluated.
`hyper_cutoff`	Non-negative cutoff used by `.hyperplane_count()` for summary output.
`verbose`	Logical; if `TRUE`, print convergence messages for the outer loop.