implicitIF_full: Full implicit influence function (beta, u, sigma, theta) for...

In robustlmm: Robust Linear Mixed Effects Models

Full implicit influence function (beta, u, sigma, theta) for a fitted rlmerMod object.

Description

Extends implicitIF by adding the \sigma-DAS and \theta-DAS scoring equations to the implicit-derivative linear system. The Jacobian of the full score wrt (\beta, u, \log \sigma, \theta) is computed via numDeriv::jacobian with Richardson extrapolation, reusing the converged DAS scales on the non-\theta columns (they depend on \theta only); the Jacobian wrt the response is closed-form. Only DASvar and DAStau methods are supported (DAStau additionally requires block sizes \le 2).

Usage

implicitIF_full(fit, eps = 1e-06, use.cache = TRUE)

Arguments

fit	An rlmerMod object.
eps	Numerical step for numDeriv::jacobian (default 1e-6).
use.cache	If TRUE (default), return a result cached on the fit when one is stored for the current \theta, and cache the result otherwise.

Details

This function is the engine behind cooks.distance / influence; users who only want Cook's distance should call those S3 methods.

The result is cached on the fit (keyed by \theta) when use.cache = TRUE, so repeated calls – and the consumers cooks.distance, the sandwich vcov, and the Satterthwaite df of summary / anova / emmeans / confint – share a single computation.

Value

A list with components IF_beta (p \times n), IF_u (q \times n), IF_sigma (1 \times n), IF_theta (L \times n), and the model-based delta-method covariance vcov_model_delta.

See Also

implicitIF, cooks.distance

robustlmm documentation built on July 30, 2026, 5:11 p.m.