Inference for generalized additive mixed models via penalized marginal likelihood
Methodology
2025-04-15 v2
Abstract
The Laplace approximation is sometimes not sufficiently accurate for smoothing parameter estimation in generalized additive mixed models. A novel estimation strategy is proposed that solves this problem and leads to estimates exhibiting the correct statistical properties.
Cite
@article{arxiv.2501.13797,
title = {Inference for generalized additive mixed models via penalized marginal likelihood},
author = {Alex Stringer},
journal= {arXiv preprint arXiv:2501.13797},
year = {2025}
}