Overview
Simon N. Wood is a statistician (University of Edinburgh; previously University of Bath), best known for generalized additive models and the widely used mgcv R package for penalized smoothing.
Key Contributions / Features
- Fast stable REML/ML for GAMs (Wood 2011): direct Laplace-approximate REML optimization of smoothing parameters — the estimation engine of
mgcv.
- Generalized Additive Models: An Introduction with R — the standard textbook on penalized-spline GAMs.
- Thin-plate regression splines, tensor-product smooths, and stable/scalable methods for large additive models; also work on statistical ecology and dynamical-system inference.
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