The SPDE approach to smoothing can be understood within the basis-penalty GAM framework.
Allowing for the relationship between predictors and a response to change over time: incorporating flexible generalised additive models (GAMs) with Markov-switching.
I am a Biometrika Research Fellow at the University of St Andrews, based in the Centre for Research into Ecological and Environmental Modelling.
My research focusses on stochastic processes that are latent or partially observed. This usually involves stochastic differential equations, hidden Markov models, smoothing techniques, and high-dimensional integrals. Listed below are some of my interests.
My PhD was about Incorporating Animal Movement with Distance Sampling and Spatial Capture-Recapture and was supervised by Stephen T. Buckland and Roland Langrock.
Each published paper has a link to the published version. Submitted papers have a link to the current draft where possible.
Software available from my GitHub page.
CTMCdive: R package to fit continuous-time Markov chain model with temporaly-varying smooth transition intensities (intended to model cetacean dive and surface durations).
openpopscr: R package to fit open population Jolly-Seber spatial capture-recapture models by maximum likelihood.
SimDs: source code to simulation line transect distance sampling surveys with animals moving in 2D.