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Refit a fast AME model with a warm start

Source: R/ame_als_bootstrap.R
ame_als_refit.Rd

Refits an AME model by iterative block coordinate descent, initialised (“warm-started”) from an existing ame_als fit. This is the workhorse of ame_als_bootstrap: every bootstrap replicate is refit from the original point estimate rather than from a cold random start, which prevents replicates from converging to different local optima or rotations and is essential for meaningful bootstrap standard errors.

Usage

ame_als_refit(
  object,
  Y_new = NULL,
  X_new = NULL,
  Z_new = NULL,
  max_iter = 30,
  tol = 1e-05,
  verbose = FALSE
)

Arguments

object

an ame_als object supplying the warm-start values (mu, beta, a, b, U, V) and the model configuration (family, mode, symmetric, R).

Y_new

optional canonical outcome array [n_row, n_col, T] to refit on. Defaults to object$Y.

X_new

optional canonical design array [n_row, n_col, p, T]. Defaults to object$X.

Z_new

optional canonical working-response array [n_row, n_col, T]. When supplied, the model is refit by a Gaussian block coordinate descent directly on Z_new, bypassing the family transform / IRLS reweighting. This is used by the parametric bootstrap of a non-normal transform fit, whose estimator is a Gaussian fit to a fixed transformed response. Y_new is still used for the observed-cell pattern.

max_iter

maximum block coordinate descent iterations (default 30; fewer are needed than for a cold start).

tol

convergence tolerance (default 1e-5).

verbose

logical; print progress (default FALSE).

Value

An object of class "ame_als"; see ame_als.

Details

The estimation algorithm is the iterative block coordinate descent estimator of the Social Influence Regression model of Hoff & Minhas (sir::sir_alsfit()), adapted to the AME model, with each bootstrap replicate warm-started from the original point estimate.

References

Minhas, S. and Hoff, P. D. (2025). Decomposing Network Dynamics: Social Influence Regression. Political Analysis. The iterative block coordinate descent estimator refit here originates with that work (implemented in sir::sir_alsfit()).

See also

ame_als, ame_als_bootstrap.

Author

Cassy Dorff, Shahryar Minhas, Tosin Salau

Examples

Y <- matrix(rnorm(400), 20, 20); diag(Y) <- NA
fit <- ame_als(Y, R = 1, family = "normal", verbose = FALSE)
refit <- ame_als_refit(fit, verbose = FALSE)
coef(refit)
#>  intercept 
#> 0.09635372