Simon Wood

Simon N Wood

Mathematical Sciences (4W5.14), University of Bath, Bath, BA2 7AY UK; +44 (0)1225 386603; s.wood _at_ bath.ac.uk

Please contact me if you would be interested in doing a PhD on parallelization of Generalized additive models, with particular focus on electricity load forcasting with EDF. Funding is available for UK students and EU students who have been resident in the UK for 3 years (other EU students are eligible for Fees only funding).

Apologies if I have not replied to you on an mgcv related query: I've got rather behind on mgcv email, especially on the interesting stuff that requires thought.

I work as a professor in the statistics group at the university of Bath (part time as I have two small children). I have two main research interests.

Smoothing. In particular methods for generalized additive modelling and applications of generalized additive models (GAMs). I am especially interested in smoothness selection, and low rank spline smoothing, and have written an R package called mgcv which implements GAMs. Some recent example smoothing papers are
- Wood, SN (2008) Fast stable direct fitting and smoothness selection for Generalized Additive Models. JRSSB 70(3), 495-518.
- Wood, SN, MV Bravington and SL Hedley (2008) Soap film smoothing. JRSSB, 70(5), 931-955.
- Wood, SN (2011) Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. JRSSB, 73(1), 3-36
Statistical Ecology. In particular using ecological dynamic models as statistical models to help understand ecological mechanisms, and ecological applications of nonlinear random effects models and smooth models, as part of NCSE. Some recent example statistical ecology papers are
- Low, C, SN Wood and RM Nisbet (2009) The effects of group size, leaf size, and density on the performance of a leaf-mining moth. Journal of Animal Ecology 78(1): 152-160
- Augustin, NH, M Musio, K von Wilpert, E Kublin, SN Wood, and M Schumacher (2009) Modelling spatio-temporal forest health monitoring data. JASA 104, 899-911.
- Wood SN (2010) Statistical inference for noisy nonlinear ecological dynamic systems. Nature 466(26): 1102-1104. (or short web version with links to supplementary material and methods ).

Fuller lists of papers are at researcherid and google scholar (home-made version with added mistakes here.). In 2006 I published a book called Generalized Additive Models: An Introduction with R , which explains the smooth modelling part of my work in some detail.

PhD students:

Matteo Fasiolo, works on statistics for ecological dynamic systems.
Dr. Natalya Pya, worked on shape preserving smoothing and is now a PDRA working on statistical ecology.
David Miller has recently defended a thesis on finite area smoothing.

Here is a selection of talks. It's not exhaustive, but hopefully gives some idea of what I work on.

REML estimation of GAMs
GAMs and mgcv
An introduction to GAMs
Implementing mgcv in R
Soap film smoothing how to smooth over domains were the boundary matters.
Inaugural lecture with slides. [12/3/2009. A university of Bath podcast ]
GAM overview [invited talk at the excellent IWSM Barcelona, 2007]
Tensor product smoothing and GAMMs [Given in various forms, in various places].
Calanus in the North Atlantic - a large complex model estimation and testing problem. [St Andrews, RSS and elsewhere].
Slides from a couple of short GAM course .

I am teaching 2 courses this year

Statistical Computing for statistics PhD students via APTS . The notes are available from this page
A course on using the MLE and Bayesian approaches to statistics in practice: Applied Statistical Inference.

Here are a couple of examples of previous courses

mgcv - generalized additive (mixed) models and other generalized ridge regression for R.
Software
C.V. (not up to date).
Bath maps