1.4k citations · 1.9k across the 16 of their papers we have counts for
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Spatial+: a novel approach to spatial confounding
Emiko Dupont, Simon N. Wood, Nicole Augustin
In spatial regression models, collinearity between covariates and spatial effects can lead to significant bias in effect estimates. This problem, known as spatial confounding, is e…
qgam: Bayesian non-parametric quantile regression modelling in R
Matteo Fasiolo, Simon N. Wood, Margaux Zaffran +2
Generalized additive models (GAMs) are flexible non-linear regression models, which can be fitted efficiently using the approximate Bayesian methods provided by the mgcv R package.…
Additive stacking for disaggregate electricity demand forecasting
Christian Capezza, Biagio Palumbo, Yannig Goude +2
Future grid management systems will coordinate distributed production and storage resources to manage, in a cost effective fashion, the increased load and variability brought by th…
COVID-19 and the difficulty of inferring epidemiological parameters from clinical data
Simon N. Wood, Ernst C. Wit, Matteo Fasiolo +1
Knowing the infection fatality ratio (IFR) is of crucial importance for evidence-based epidemic management: for immediate planning; for balancing the life years saved against the l…
Inferring UK COVID-19 fatal infection trajectories from daily mortality data: were infections already in decline before the UK lockdowns?
Simon N. Wood
The number of new infections per day is a key quantity for effective epidemic management. It can be estimated relatively directly by testing of random population samples. Without s…