CHANGES IN VERSION 1.4.0 (January 2026)

These change notes reflect changes in functionality relative to the implementation of Laplace/AGHQ approximation in the nimble package, version 1.3.0.

USER LEVEL CHANGES

• Move Laplace/AGHQ approximation from nimble to nimbleQuad package.

• Add a nested approximation method that provides approximate posterior inference using methodology similar to the well-known INLA approach (implemented in the R-INLA package) and to the related methods for extended Gaussian latent models (EGLMs) of Stringer et al. (2023), implemented in the aghq R package.

• Greatly improve efficiency of Laplace/AGHQ approximation through major revision of derivative calculations, including removal of “computeMethod” options (PR 52).

• Greatly improve efficiency of Laplace/AGHQ approximation when using the multivariate normal distribution, via a new dmnormAD version of the distribution customized for efficient computation with NIMBLE’s AD system.

• Greatly improve efficiency of building Laplace/AGHQ when determining parameter dependencies in setup_OneAGHQuad (PR 48).

• Greatly improve efficiency of Laplace/AGHQ summary computation of Hessian.

• Automatically make use of analytic gradient and Hessian with respect to the random variables for univariate and multivariate normal distributions rather than AD in Laplace/AGHQ approximation. This also causes the “outer” Laplace/AGHQ optimization to not use the AD-based gradient.

• Greatly improve the efficiency of building overall Laplace approximation when using many individual Laplace approximations (PR #59).

• Inform user when overall Laplace approximation is decomposed into multiple Laplace approximations.

• Improve messaging when Laplace/AGHQ approximation does not converge.

• Provide a variety of quadrature grids, extending from standard AGHQ, including grid pruning, sparse grids, and allowing user-provided grids.

• Automatically remove random effect nodes with no dependent data from Laplace (Issue #56).

• Add ability to find posterior mode (as well as prior-penalized MLE, as used in fisheries) via Laplace approximation.

BUG FIXES

• Fix handling of fnscale when updateSettings is used.

• Fix buildAGHQ for case with no random effects.

• Fix length of latent nodes in Laplace/AGHQ under non-1:1 transformation (PR #41).

• Fix seg fault when “model” option passed as innerOptimStart (Issue #62).

DEVELOPER LEVEL CHANGES

• Completely refactor and generalize the quadrature grids implementation, including making consistent with mvQuad.